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Faculty / Organisational entity
Trimming of surfaces and volumes, curve and surface modeling via Bézier's idea of destortion, segmentation, reparametrization, geometric continuity are examples of applications of functional composition. This paper shows how to
compose polynomial and rational tensor product Bézier representations. The problem of composing Bezier splines and B-spline representations will also be addressed in this paper.
Today, test methods for communication protocols assume, among other things, that the protocol design is specified as a single, monolithic finite state machine (FSM). From this specification, test suites that are capable of detecting output and/or transfer faults in the protocol implementation are derived. Limited applicability ofthese methods is mainly because oftheir specific assumptions, and due to the size of the derived test suite and the resulting test effort for realistic protocols. In this work, the compositional test method (C-method), which exploits the available structure of a communication protocol, is proposed. The C-method first tests each protocol component separately for output and/or transfer faults, using one of the traditional test methods, then checks for composability, and finally tests the composite system for composition faults. To check for composability and to derive the test suite for the detection of composition faults, it is not required to construct the global state machine. Instead, all information is derived from the component state machines, which avoids a potential state explosion and lengthy test cases. Furthermore, the test suite checks for composition faults only. This substantially reduces the size of the test suite and thus the overall test effort.
Es handelt sich um den Aufbau des ersten Roboter-gestützten Systems zum Fräsen an der lateralen Schädelbasis. Durch Rückkopplung der Sensordaten lässt sich ein menschähnliches Fräsen nachahmen. Mehr noch: Es besteht die Möglichkeit der automatisierten Detektion der Dura mater durch Analyse der Standardabweichung der Kräfte, da die Dura mater dämpfend auf den Fräser wirkt. Mit dem Roboter ist es möglich, ein exaktes Implantatbett im Bereich der lateralen Schädelbasis auszufräsen.
In recent years, Smolyak quadrature rules (also called hyperbolic cross points or sparse grids) have gained interest as a possible competitor to number theoretic quadratures for high dimensional problems. A standard way of comparing the quality of multivariate quadrature formulas
consists in computing their \(L_2\)-discrepancy. Especially for larger dimensions, such computations are a highly complex task. In this paper we develop a fast recursive algorithm for computing the \(L_2\)-discrepancy (and related quality measures) of general Smolyak quadratures. We carry out numerical comparisons between the discrepancies of certain Smolyak rules, Hammersley and Monte Carlo sequences.
A notion of discrepancy is introduced, which represents the integration error on spaces of \(r\)-smooth periodic functions. It generalizes the diaphony and constitutes a periodic counterpart to the classical \(L_2\)-discrepancy as weil as \(r\)-smooth versions of it introduced recently by Paskov [Pas93]. Based on previous work [FH96], we develop an efficient algorithm for computing periodic discrepancies for quadrature formulas possessing certain tensor product structures, in particular, for Smolyak quadrature rules (also called sparse grid methods). Furthermore, fast algorithms of computing periodic discrepancies for lattice rules can easily be derived from well-known properties of lattices. On this basis we carry out numerical comparisons of discrepancies between Smolyak and lattice rules.
In order to discuss the kinds of reasoning a visualization supports and the conclusions that can be drawn within the analysiscontext, a theoretical framework is needed that enables a formal treatment of the reasoning process. Such a model needs toencompass three stages of the visualization pipeline: encoding, decoding and interpretation. The encoding details how dataare transformed into a visualization and what can be seen in the visualization. The decoding explains how humans constructgraphical contexts inside the depicted visualization and how they interpret them assigning meaning to displayed structuresaccording to a formal reasoning strategy. In the presented model, we adapt and combine theories for the different steps intoa unified formal framework such that the analysis process is modelled as an assignment of meaning to displayed structuresaccording to a formal reasoning strategy. Additionally, we propose the ConceptGraph, a combined graph-based representationof the finite-state transducers resulting from the three stages, that can be used to formalize and understand the reasoning process.We apply the new model to several visualization types and investigate reasoning strategies for various tasks.
We propose a specification language for the formalization of data types with par-tial or non-terminating operations as part of a rewrite-based logical frameworkfor inductive theorem proving. The language requires constructors for designat-ing data items and admits positive/negative conditional equations as axioms inspecifications. The (total algebra) semantics for such specifications is based onso-called data models. We present admissibility conditions that guarantee theunique existence of a distinguished data model with properties similar to thoseof the initial model of a usual equational specification. Since admissibility of aspecification requires confluence of the induced rewrite relation, we provide aneffectively testable confluence criterion which does not presuppose termination.
There are well known examples of monoids in literature which do not admit a finite andcanonical presentation by a semi-Thue system over a fixed alphabet, not even over an arbi-trary alphabet. We introduce conditional Thue and semi-Thue systems similar to conditionalterm rewriting systems as defined by Kaplan. Using these conditional semi-Thue systems wegive finite and canonical presentations of the examples mentioned above. Furthermore weshow, that each finitely generated monoid with decidable word problem is embeddable in amonoid which has a finite canonical conditional presentation.
We present a new criterion for confluence of (possibly) non-terminating left-linear term rewriting systems. The criterion is based on certain strong joinabil-ity properties of parallel critical pairs . We show how this criterion relates toother well-known results, consider some special cases and discuss some possibleextensions.
Visual Search has been investigated by many researchers inspired by the biological fact, that the sensory elements on the mammal retina are not equably distributed. Therefore the focus of attention (the area of the retina with the highest density of sensory elements) has to be directed in a way to efficiently gather data according to certain criteria. The work discussed in this article concentrates on applying a laser range finder instead of a silicon retina. The laser range finder is maximal focused at any time, but therefore a low resolution total-scene-image, available with camera-like devices from scratch on, cannot be used here. By adapting a couple of algorithms, the edge-scanning module steering the laser range finder is able to trace a detected edge. Based on the data scanned so far , two questions have to be answered. First: "Should the actual (edge-) scanning be interrupted in order to give another area of interest a chance of being investigated?" and second: "Where to start a new edge-scanning, after being interrupted?". These two decision-problems might be solved by a range of decision systems. The correctness of the decisions depends widely on the actual environment and the underlying rules may not be well initialized with a-priori knowledge. So we will present a version of a reinforcement decision system together with an overall scheme for efficiently controlling highly focused devices.
This paper is to present a new algorithm, called KNNcost, for learning feature weights for CBR systems used for classification. Unlike algorithms known so far, KNNcost considers the profits of a correct and the cost of a wrong decision. The need for this algorithm is motivated from two real-world applications, where cost and profits of decisions play a major role. We introduce a representation of accuracy, cost and profits of decisions and define the decision cost of a classification system. To compare accuracy optimization with cost optimization, we tested KNNacc against KNNcost. The first one optimizes classification accuracy with a conjugate gradient algorithm. The second one optimizes the decision cost of the CBR system, respecting cost and profits of the classifications. We present experiments with these two algorithms in a real application to demonstrate the usefulness of our approach.
Ever since Mark Weiser’s vision of Ubiquitous Computing the importance of context has increased in the computer science domain. Future Ambient Intelligent Environments will assist humans in their everyday activities, even without them being constantly aware of it. Objects in such environments will have small computers embedded into them which have the ability to predict human needs from the current context and adapt their behavior accordingly. This vision equally applies to future production environments. In modern factories workers and technical staff members are confronted with a multitude of devices from various manufacturers, all with different user interfaces, interaction concepts and degrees of complexity. Production processes are highly dynamic, whole modules can be exchanged or restructured. Both factors force users to continuously change their mental model of the environment. This complicates their workflows and leads to avoidable user errors or slips in judgement. In an Ambient Intelligent Production Environment these challenges have to be approached. The SmartMote is a universal control device for ambient intelligent production environments like the SmartFactoryKL. It copes with the problems mentioned above by integrating all the user interfaces into a single, holistic and mobile device. Following an automated Model-Based User Interface Development (MBUID) process it generates a fully functional graphical user interface from an abstract task-based description of the environment during run-time. This work introduces an approach to integrating context, namely the user’s location, as an adaptation basis into the MBUID process. A Context Model is specified, which stores location information in a formal and precise way. Connected sensors continuously update the model with new values. The model is complemented by a reasoning component which uses an extensible set of rules. These rules are used to derive more abstract context information from basic sensor data and for providing this information to the MBUID process. The feasibility of the approach is shown by using the example of Interaction Zones, which let developers describe different task models depending on the user’s location. Using the context model to determine when a user enters or leaves a zone, the generator can adapt the graphical user interface accordingly. Context-awareness and the potential to adapt to the current context of use are key requirements of applications in ambient intelligent environments. The approach presented here provides a clear procedure and extension scheme for the consideration of additional context types. As context has significant influence on the overall User Experience, this results not only in a better usefulness, but also in an improved usability of the SmartMote.
In recent years, recommender systems have been widely used for a variety of different kinds of items such as books, movies, and music. However, current recommendation approaches have often been criticized to suffer from overspecialization thus not enough considering a user’s diverse topics of interest. In this thesis we present a novel approach to extracting contextualized user profiles which enable recommendations taking into account a user’s full range of interests. The method applies algorithms from the domain of topic detection and tracking to automatically identify diverse user interests and to represent them with descriptive labels. That way manual annotations of interest topics by the users, e. g., from a predefined domain taxonomy, are no longer required. The approach has been tested in two scenarios: First, we implemented a content-based recommender system for an Enterprise 2.0 resource sharing platform where the contextualized user interest profiles have been used to generate recommendations with a high degree of inter-topic diversity. In an effort to harness the collective intelligence of the users, the resources in the system were described by making use of user-generated metadata. The evaluation experiments show that our approach is likely to capture a multitude of diverse interest topics per user. The labels extracted are specific for these topics and can be used to retrieve relevant on-topic resources. Second, a slightly adapted variation of the algorithm has been used to target music recommendations based on the user’s current mood. In this scenario music artists are described by using freely available Semantic Web data from the Linked Open Data cloud thus not requiring expensive metadata annotations by experts. The evaluation experiments conducted show that many users have a multitude of different preferred music styles. However a correlation between these music styles and music mood categories could not be observed. An integration of our proposed user profiles with existing user model ontologies seems promising for enabling context-sensitive recommendations.
Under the notion of Cyber-Physical Systems an increasingly important research area has
evolved with the aim of improving the connectivity and interoperability of previously
separate system functions. Today, the advanced networking and processing capabilities
of embedded systems make it possible to establish strongly distributed, heterogeneous
systems of systems. In such configurations, the system boundary does not necessarily
end with the hardware, but can also take into account the wider context such as people
and environmental factors. In addition to being open and adaptive to other networked
systems at integration time, such systems need to be able to adapt themselves in accordance
with dynamic changes in their application environments. Considering that many
of the potential application domains are inherently safety-critical, it has to be ensured
that the necessary modifications in the individual system behavior are safe. However,
currently available state-of-the-practice and state-of-the-art approaches for safety assurance
and certification are not applicable to this context.
To provide a feasible solution approach, this thesis introduces a framework that allows
“just-in-time” safety certification for the dynamic adaptation behavior of networked
systems. Dynamic safety contracts (DSCs) are presented as the core solution concept
for monitoring and synthesis of decentralized safety knowledge. Ultimately, this opens
up a path towards standardized service provision concepts as a set of safety-related runtime
evidences. DSCs enable the modular specification of relevant safety features in
networked applications as a series of formalized demand-guarantee dependencies. The
specified safety features can be hierarchically integrated and linked to an interpretation
level for accessing the scope of possible safe behavioral adaptations. In this way, the networked
adaptation behavior can be conditionally certified with respect to the fulfilled
DSC safety features during operation. As long as the continuous evaluation process
provides safe adaptation behavior for a networked application context, safety can be
guaranteed for a networked system mode at runtime. Significant safety-related changes
in the application context, however, can lead to situations in which no safe adaptation
behavior is available for the current system state. In such cases, the remaining DSC
guarantees can be utilized to determine optimal degradation concepts for the dynamic
applications.
For the operationalization of the DSCs approach, suitable specification elements and
mechanisms have been defined. Based on a dedicated GUI-engineering framework it is
shown how DSCs can be systematically developed and transformed into appropriate runtime
representations. Furthermore, a safety engineering backbone is outlined to support
the DSC modeling process in concrete application scenarios. The conducted validation
activities show the feasibility and adequacy of the proposed DSCs approach. In parallel,
limitations and areas of future improvement are pointed out.
In robotics, information is often regarded as a means to an end. The question of how to structure information and how to bridge the semantic gap between different levels of abstraction in a uniform way is still widely regarded as a technical issue. Ignoring these challenges appears to lead robotics into a similar stasis as experienced in the software industry of the late 1960s. From the beginning of the software crisis until today, numerous methods, techniques, and tools for managing the increasing complexity of software systems have evolved. The attempt to transfer several of these ideas towards applications in robotics yielded various control architectures, frameworks, and process models. These attempts mainly provide modularisation schemata which suggest how to decompose a complex system into less complex subsystems. The schematisation of representation and information flow however is mostly ignored. In this work, a set of design schemata is proposed which is embedded into an action/perception-oriented design methodology to promote thorough abstractions between distinct levels of control. Action-oriented design decomposes control systems top-down and sensor data is extracted from the environment as required. This comes with the problem that information is often condensed in a premature fashion. That way, sensor processing is dependent on the control system design resulting in a monolithical system structure with limited options for reusability. In contrast, perception-oriented design constructs control systems bottom-up starting with the extraction of environment information from sensor data. The extracted entities are placed into structures which evolve with the development of the sensor processing algorithms. In consequence, the control system is strictly dependent on the sensor processing algorithms which again results in a monolithic system. In their particular domain, both design approaches have great advantages but fail to create inherently modular systems. The design approach proposed in this work combines the strengths of action orientation and perception orientation into one coherent methodology without inheriting their weaknesses. More precisely, design schemata for representation, translation, and fusion of environmental information are developed which establish thorough abstraction mechanisms between components. The explicit introduction of abstractions particularly supports extensibility and scalability of robot control systems by design.
We describe a hybrid case-based reasoning system supporting process planning for machining workpieces. It integrates specialized domain dependent reasoners, a feature-based CAD system and domain independent planning. The overall architecture is built on top of CAPlan, a partial-order nonlinear planner. To use episodic problem solving knowledge for both optimizing plan execution costs and minimizing search the case-based control component CAPlan/CbC has been implemented that allows incremental acquisition and reuse of strategical problem solving experience by storing solved problems as cases and reusing them in similar situations. For effective retrieval of cases CAPlan/CbC combines domain-independent and domain-specific retrieval mechanisms that are based on the hierarchical domain model and problem representation.
We describe a hybrid case-based reasoning system supporting process planning for machining workpieces. It integrates specialized domain dependent reasoners, a feature-based CAD system and domain independent planning. The overall architecture is build on top of CAPlan, a partial-order nonlinear planner. To use episodic problem solving knowledge for both optimizing plan execution costs and minimizing search the case-based control component CAPlan/CbC has been realized that allows incremental acquisition and reuse of strategical problem solving experience by storing solved problems as cases and reusing them in similar situations. For effective retrieval of cases CAPlan/CbC combines domain-independent and domain-specific retrieval mechanisms that are based on the hierarchical domain model and problem representation.
Top-down and bottom-up theorem proving approaches have each specific ad-vantages and disadvantages. Bottom-up provers profit from strong redundancycontrol and suffer from the lack of goal-orientation, whereas top-down provers aregoal-oriented but have weak calculi when their proof lengths are considered. Inorder to integrate both approaches our method is to achieve cooperation betweena top-down and a bottom-up prover: The top-down prover generates subgoalclauses, then they are processed by a bottom-up prover. We discuss theoreticaspects of this methodology and we introduce techniques for a relevancy-basedfiltering of generated subgoal clauses. Experiments with a model eliminationand a superposition-based prover reveal the high potential of our cooperation approach.The author was supported by the Deutsche Forschungsgemeinschaft (DFG).
We present a cooperation concept for automated theorem provers that isbased on a periodical interchange of selected results between several incarnationsof a prover. These incarnations differ from each other in the search heuristic theyemploy for guiding the search of the prover. Depending on the strengths' andweaknesses of these heuristics different knowledge and different communicationstructures are used for selecting the results to interchange.Our concept is easy to implement and can easily be integrated into alreadyexisting theorem provers. Moreover, the resulting cooperation allows the dis-tributed system to find proofs much faster than single heuristics working alone.We substantiate these claims by two case studies: experiments with the DiCoDesystem that is based on the condensed detachment rule and experiments with theSPASS system, a prover for first order logic with equality based on the super-position calculus. Both case studies show the improvements by our cooperationconcept.
Coordinating distributed software development projectsbecomes more difficult, as software becomes more complex, team sizes and organisational overheads increase,and software components are sourced from disparate places. We describe the development of a range of softwaretools to support coordination of such projects. Techniques we use include asynchronous and semi -synchronousediting, software process modelling and enactment, developer-specified coordination agents, and component-based tool integration.
Coordinating distributed processes, especially engineering and software design processes, has been a research topic for some time now. Several approaches have been published that aim at coordinating large projects in general, and large software development processes in specific. However, most of these approaches focus on the technical part of the design process and omit management activities like planning and scheduling the project, or monitoring it during execution. In this paper, we focus on coordinating the management activities that accompany the technical software design process. We state the requirements for a Software Engineering Environm ent (SEE) accommodating management, and we describe a possible architecture for such an SEE.
In the recent years a form of software development that was previously dismissed as too ad-hoc and chaotic for serious projects has suddenly taken the front stage. With products such as Apache, Linux, Perl, and others, open-source software has emerged as a viable alternative to traditional approaches to software development. With its globally distributed developer force and extremely rapid code evolution, open source is arguably the extreme in "virtual software projects" [1], and exemplifies many of the advantages and challenges of distributed software development.
In this paper we describe how explicit models of software or knowledge engineering processes can be used to guide and control the distributed development of complex systems. The paper focuses on techniques which automatically infer dependencies between decisions from a process model and methods which allow to integrate planning and execution steps. Managing dependencies between decisions is a basis for improving the traceability of develop- ment processes. Switching between planning and execution of subprocesses is an inherent need in the development of complex systems. The paper concludes with a description of the CoMo-Kit system which implements the technolo- gies mentioned above and which uses WWW technology to coordinate development processes. An on-line demonstration of the system can be found via the CoMo-Kit homepage:
CORBA Lacks Venom
(1999)
Distributed objects bring to distributed computing such desirable properties of modularisation, abstraction and reuse easing the burden of development and maintenance by diminishing the gap between implementation and real-world objects. Distributed objects, however, need a consistent framework in which inter-object communication may take place. The Common Object Request Broker Architecture (CORBA) is a distributed object standard. CORBA's primary protocol is the Internet Interoperable Object Protocol limited to blocked synchronous remote procedure calls, over TCP/IP which is inappropriate for systems requiring timely guarantees.
Shared memory concurrency is the pervasive programming model for multicore architectures
such as x86, Power, and ARM. Depending on the memory organization, each architecture follows
a somewhat different shared memory model. All these models, however, have one common
feature: they allow certain outcomes for concurrent programs that cannot be explained
by interleaving execution. In addition to the complexity due to architectures, compilers like
GCC and LLVM perform various program transformations, which also affect the outcomes of
concurrent programs.
To be able to program these systems correctly and effectively, it is important to define a
formal language-level concurrency model. For efficiency, it is important that the model is
weak enough to allow various compiler optimizations on shared memory accesses as well
as efficient mappings to the architectures. For programmability, the model should be strong
enough to disallow bogus “out-of-thin-air” executions and provide strong guarantees for well-synchronized
programs. Because of these conflicting requirements, defining such a formal
model is very difficult. This is why, despite years of research, major programming languages
such as C/C++ and Java do not yet have completely adequate formal models defining their
concurrency semantics.
In this thesis, we address this challenge and develop a formal concurrency model that is very
good both in terms of compilation efficiency and of programmability. Unlike most previous
approaches, which were defined either operationally or axiomatically on single executions,
our formal model is based on event structures, which represents multiple program executions,
and thus gives us more structure to define the semantics of concurrency.
In more detail, our formalization has two variants: the weaker version, WEAKEST, and the
stronger version, WEAKESTMO. The WEAKEST model simulates the promising semantics proposed
by Kang et al., while WEAKESTMO is incomparable to the promising semantics. Moreover,
WEAKESTMO discards certain questionable behaviors allowed by the promising semantics.
We show that the proposed WEAKESTMO model resolve out-of-thin-air problem, provide
standard data-race-freedom (DRF) guarantees, allow the desirable optimizations, and can be
mapped to the architectures like x86, PowerPC, and ARMv7. Additionally, our models are
flexible enough to leverage existing results from the literature to establish data-race-freedom
(DRF) guarantees and correctness of compilation.
In addition, in order to ensure the correctness of compilation by a major compiler, we developed
a translation validator targeting LLVM’s “opt” transformations of concurrent C/C++
programs. Using the validator, we identified a few subtle compilation bugs, which were reported
and were fixed. Additionally, we observe that LLVM concurrency semantics differs
from that of C11; there are transformations which are justified in C11 but not in LLVM and
vice versa. Considering the subtle aspects of LLVM concurrency, we formalized a fragment
of LLVM’s concurrency semantics and integrated it into our WEAKESTMO model.
This PhD thesis aims at finding a global robot navigation strategy for rugged off-road terrain which is robust against inaccurate self-localization, scalable to large environments, but also cost-efficient, e.g. able to generate navigation paths which optimize a cost measure closely related to terrain traversability. In order to meet this goal, aspects of both metrical and topological navigation techniques are combined. A primarily topological map is extended with the previously lacking capability of cost-efficient path planning and map extension. Further innovations include a multi-dimensional cost measure for topological edges, a method to learn these costs based on live feedback from the robot and a set of extrapolation methods to predict the traversability costs for untraversed edges. The thesis presents two sophisticated new image analysis techniques to optimize cost prediction based on the shape and appearance of surrounding terrain. Experimental results indicate that the proposed global navigation system is indeed able to perform cost-efficient, large scale path planning. At the same time, the need to maintain a fine-grained, global world model which would reduce the scalability of the approach is avoided.
We examine different possibilities of coupling saturation-based theorem pro-vers by exchanging positive/negative information. We discuss which positive ornegative information is well-suited for cooperative theorem proving and show inan abstract way how this information can be used. Based on this study, we in-troduce a basic model for cooperative theorem proving. We present theoreticalresults regarding the exchange of positive/negative information as well as practi-cal methods and heuristics that allow for a gain of efficiency in comparison withsequential provers. Finally, we report on experimental studies conducted in theareas condensed detachment, unfailing completion, and superposition.The author was supported by the Deutsche Forschungsgemeinschaft (DFG).
Self-adaptation allows software systems to autonomously adjust their behavior during run-time by handling all possible
operating states that violate the requirements of the managed system. This requires an adaptation engine that receives adaptation
requests during the monitoring process of the managed system and responds with an automated and appropriate adaptation
response. During the last decade, several engineering methods have been introduced to enable self-adaptation in software systems.
However, these methods lack addressing (1) run-time uncertainty that hinders the adaptation process and (2) the performance
impacts resulted from the complexity and the large number of the adaptation space. This paper presents CRATER, a framework
that builds an external adaptation engine for self-adaptive software systems. The adaptation engine, which is built on Case-based
Reasoning, handles the aforementioned challenges together. This paper is braced with an experiment illustrating the benefits of
this framework. The experimental results shows the potential of CRATER in terms handling run-time uncertainty and adaptation
remembrance that enhances the performance for large number of adaptation space.
Fallbasiertes Schliessen (engl.: Case-based Reasoning) hat in den vergangenen Jahren zunehmende Bedeutung für den praktischen Einsatz in realen Anwendungsbereichen erlangt. In dieser Arbeit werden zunächst die allgemeine Vorgehensweise und die verschiedenen Teilaufgaben des fallbasierten Schliessens vorgestellt. Anschliessend wird auf die charakteristischen Eigenschaften eines Anwendungsbereiches eingegangen und an der konkreten Aufgabe der Kreditwürdigkeitsprüfung die Realisierung eines fallbasierten Ansatzes in der Finanzwelt beschrieben.
David Chapman hat 1987 mit seinem Artikel Planning for Conjunctive Goals einen wichtigen Schritt in Richtung der Formalisierung von partiell ordnen der Planung und ihrem Verständnis gemacht. Grundlegendes Konzept von David Chapman ist die Idee modaler Wahrheit in Plänen; sein Modal Truth Criterion (MTC) macht Aussagen über die Gültigkeit einer Aussage in einem partiell geordneten Plan. Kambhampati und Nau zeigten mit ihrem Papier On the Nature of Modal Truth Criteria in Planning einige wesentliche Mängel bzw. begriffliche Ungenauigkeiten an Chapmans Kriterium auf und machten mit ihrem Modal Conditional Truth Criterion Vorschläge für eine Korrektur. Insbesondere bekam die Frage nach der Ausführbarkeit eines Planes hier ein grösseres Gewicht. Ziel dieser Projektarbeit ist es zunächst, das MTC von Chapman sowie die Modifikation darzustellen und, als praktische Aufgabe, die Realisierung des MTC für den Causal Link Planer CAPlan, basierend auf der bestehenden Implementation des Systems.
Data-driven and Sparse-to-Dense Concepts in Scene Flow Estimation for Automotive Applications
(2022)
Highly assisted driving and autonomous vehicles require a detailed and accurate perception of the environment. This includes the perception of the 3D geometry of the scene and the 3D motion of other road users. The estimation of both based on images is known as the scene flow problem in computer vision. This thesis deals with a solution to the scene flow problem that is suitable for application in autonomous vehicles. This application imposes strict requirements on accuracy, robustness, and speed. Previous work was lagging behind in at least one of these metrics. To work towards the fulfillment of those requirements, the sparse-to-dense concept for scene flow estimation is introduced in this thesis. The idea can be summarized as follows: First, scene flow is estimated for some points of the scene for which this can be done comparatively easily and reliably. Then, an interpolation is performed to obtain a dense estimate for the entire scene. Because of the separation into two steps, each part can be optimized individually. In a series of experiments, it is shown that the proposed methods achieve competitive results and are preferable to previous techniques in some aspects. As a second contribution, individual components in the sparse-to-dense pipeline are replaced by deep learning modules. These are a highly localized and highly accurate feature descriptor to represent pixels for dense matching, and a network for robust and generic sparse-to-dense interpolation. Compared to end-to-end architectures, the advantage of deep modules is that they can be trained more effciently with data from different domains. The recombination approach applies a similar concept as the sparse-to-dense approach by solving and combining less diffcult, auxiliary sub-problems. 3D geometry and 2D motion are estimated separately, the individual results are combined, and then also interpolated into a dense scene flow. As a final contribution, the thesis proposes a set of monolithic end-to-end networks for scene flow estimation.
This paper introduces a new high Level programming language for a novel
class of computational devices namely data-procedural machines. These machines are by up to several orders of magnitude more efficient than the von Neumann paradigm of computers and are as flexible and as universal as computers. Their efficiency and flexibility is achieved by using field-programmable logic as the essential technology platform. The paper briefly summarizes and illustrates the essential new features of this language by means of two example programs.
NoSQL-Datenbanken werden als Alternative zu klassischen relationalen Datenbanksystemen eingesetzt, um die Herausforderungen zu meistern, die „Big Data“ mit sich bringt. Big Data wird über die drei V definiert: Es sind große Datenmengen („Volume“), die schnell anwachsen („Velocity“) und heterogene Strukturen haben („Variety“). NoSQL-Datenbanken besitzen zudem meist nur sehr einfache Anfragemethoden. Um auch komplexe Datenanalysen durchzuführen, kommen meist Datenverarbeitungsframeworks wie MapReduce, Spark oder Flink zum Einsatz. Diese sind jedoch schwieriger in der Benutzung als SQL oder andere Anfragesprachen.
In dieser Arbeit wird die Datentransformationssprache NotaQL vorgestellt. Die Sprache verfolgt drei Ziele. Erstens ist sie mächtig, einfach zu erlernen und ermöglicht komplexe Transformationen in wenigen Code-Zeilen. Zweitens ist die Sprache unabhängig von einem speziellen Datenbankmanagementsystem oder einem Datenmodell. Daten können von einem System in ein anderes transformiert und Datenmodelle dementsprechend ineinander überführt werden. Drittens ist es möglich, NotaQL-Skripte auf verschiedene Arten auszuführen, sei es mittels eines Datenverarbeitsungsframeworks oder über die Abbildung in eine andere Sprache. Typische Datentransformationen werden periodisch ausgeführt, um bei sich ändernden Basisdaten die Ergebnisse aktuell zu halten. Für solche Transformationen werden in dieser Arbeit verschiedene inkrementellen Ansätze miteinander verglichen, die es möglich machen, dass NotaQL-Transformationen die vorherigen Ergebnisse wiederbenutzen und Änderungen seit der letzten Berechnung darauf anwenden können. Die NotaQL-Plattform unterstützt verschiedene inkrementelle und nicht-inkrementelle Ausführungsarten und beinhaltet eine intelligente Advisor-Komponente, um Transformationen stets auf die bestmögliche Art auszuführen. Die vorgestellte Sprache ist optimiert für die gebräuchlichen NoSQL-Datenbanken, also Key-Value-Stores, Wide-Column-Stores, Dokumenten- und Graph-Datenbanken. Das mächtige und erweiterbare Datenmodell der Sprache erlaubt die Nutzung von Arrays, verschachtelten Objekten und Beziehungen zwischen Objekten. Darüber hinaus kann NotaQL aber nicht nur auf NoSQL-Datenbanken, sondern auch auf relationalen Datenbanken, Dateiformaten, Diensten und Datenströmen eingesetzt werden. Stößt ein Benutzer an das Limit, sind Kopplungen zu Programmiersprachen und existierenden Anwendungen mittels der Entwicklung benutzerdefinierter Funktionen und Engines möglich. Die Anwendungsmöglichkeiten von NotaQL sind Datentransformationen jeglicher Art, von Big-Data-Analysen und Polyglot-Persistence-Anwendungen bis hin zu Datenmigrationen und -integrationen.
Dealing with Dependence in the End-to-End Performance Analysis in Stochastic Network Calculus
(2022)
Communication networks, in particular the Internet, have become a pivotal part of our life. Since their beginnings, a key aspect of their applicability has been the performance. Safety-critical applications, for example, can sometimes only be implemented in a responsible manner if guarantees about their end-to-end delay can be made. A mathematical modeling and performance evaluation of communication networks requires a powerful set of tools that is able to incorporate their increasing complexity.
The stochastic network calculus (SNC) is a versatile, mathematical framework that allows for a calculation of probabilistic end-to-end performance bounds of distributed systems. Its flexibility enables to incorporate a large class of different schedulers as well as different models of traffic processes beyond the assumption of Poisson arrivals that is predominant in queueing theory-based analyses. It originates in the so-called deterministic network analysis (DNC) in the 90's of the 20th century that was introduced to provide deterministic, ``hard'' guarantees that are of relevance, e.g., in the context of real-time systems. While the DNC of today can be used to calculate fast and accurate delay bounds of arbitrary feedforward networks, the SNC is still in a significantly earlier stage. In particular, method-pertinent dependencies, i.e., a phenomenon that occurs when independent flows become stochastically dependent after sharing resources in the network, can be considered a major challenge in the SNC with moment-generating functions (MGFs).
This thesis argues to contribute to the SNC in several ways. First, we show that the ``pay multiplexing only once'' (PMOO) analysis known from the DNC is also possible in the SNC. Not only does it significantly improve end-to-end delay bounds, it also needs to consider less method-pertinent dependencies. Therefore, complexity and runtimes of the calculation are greatly reduced. Second, we introduce the concept of negative dependence to the SNC with MGFs and give numerical evidence that this can further lead to better performance bounds. Third, for the larger problem of end-to-end performance bounds of tree networks, we introduce so-called ''h-mitigators'', a modification in the calculation of MGF output bounds. It is minimally invasive, all existing results and procedures are still applicable, and improves performance bounds. As a fourth contribution, we conduct extensive numerical evaluations to substantiate our claims. Moreover, we made the respective code, the ''SNC MGF toolbox'', publicly available to ensure that the results are reproducible. At last, we conduct different stochastic analyses of a popular fair scheduler, generalized processor sharing (GPS). We give an overview of the state-of-the-art analyses in the SNC and substantiate the comparison through numerical evaluations.
Machine learning algorithms are widely applied to create powerful prediction models. With increasingly complex models, humans' ability to understand the decision function (that maps from a high-dimensional input space) is quickly exceeded. To explain a model's decisions, black-box methods have been proposed that provide either non-linear maps of the global topology of the decision boundary, or samples that allow approximating it locally. The former loses information about distances in input space, while the latter only provides statements about given samples, but lacks a focus on the underlying model for precise ‘What-If'-reasoning. In this paper, we integrate both approaches and propose an interactive exploration method using local linear maps of the decision space. We create the maps on high-dimensional hyperplanes—2D-slices of the high-dimensional parameter space—based on statistical and personal feature mutability and guided by feature importance. We complement the proposed workflow with established model inspection techniques to provide orientation and guidance. We demonstrate our approach on real-world datasets and illustrate that it allows identification of instance-based decision boundary structures and can answer multi-dimensional ‘What-If'-questions, thereby identifying counterfactual scenarios visually.
This paper addresses the decomposition of proofs as a means of constructingmethods in plan-based automated theorem proving. It shows also, howdecomposition can beneficially be applied in theorem proving by analogy.Decomposition is also useful for human-style proof presentation. We proposeseveral decomposition techniques that were found to be useful in automatedtheorem proving and give examples of their application.
Deduktionssysteme
(1999)
Optical Character Recognition (OCR) is one of the central problems in pattern recognition. Its
applications have played a great role in the digitization of document images collected from het-
erogeneous sources. Many of the well-known scripts have OCR systems with sufficiently high
performance that enables OCR applications in industrial/commercial settings. However, OCR sys-
tems yield very-good results only on a narrow domain and very-specific use cases. Thus, it is still
a challenging task, and there are other exotic languages with indigenous scripts, such as Amharic,
for which no well-developed OCR systems exist.
As many as 100 million people speak Amharic, and it is an official working language of Ethiopia.
Amharic script contains about 317 different alphabets derived from 34 consonants with small changes.
The change involves shortening or elongating one of its main legs or adding small diacritics to the
right, left, top, or bottom of the consonant character. Such modifications lead the characters to have
similar shapes and make the recognition task complex, but this is particularly interesting for charac-
ter recognition research. So far, Amharic script recognition models are developed based on classical
machine learning techniques, and they are very limited in addressing the issues for Amharic OCR.
The motivation of this thesis is, therefore, to explore and tailor contemporary deep learning tech-
niques for the OCR of Amharic.
This thesis addresses the challenges in Amharic OCR through two main contributions. The first
contribution is an algorithmic contribution in which we investigate deep learning approaches that
suit the demand for Amharic OCR. The second is a technical contribution that comprises several
works towards the OCR model development; thus, it introduces a new Amharic database consisting
of collections of images annotated at a character and text-line level. It also presents a novel CNN-
based framework designed by leveraging the grapheme of characters in Fidel-Gebeta (where Fidel-
Gebeta consists of the full set of Amharic characters in matrix structure) and achieves 94.97%
overall character recognition accuracy.
In addition to character level methods, text-line level methods are also investigated and devel-
oped based on sequence-to-sequence learning. These models avoid several of the pre-processing
stages used in prior works by eliminating the need to segment individual characters. In this design,
we use a stack of CNNs, before the Bi-LSTM layers and train from end-to-end. This model out-
performs the LSTM-CTC based network, on average, by a CER of 3.75% with the ADOCR test
set. Motivated by the success of attention, in addressing the problems’ of long sequences in Neural
Machine Translation (NMT), we proposed a novel attention-based methodology by blending the
attention mechanism into CTC objective function. This model performs far better than the existing
techniques with a CER of 1.04% and 0.93% on printed and synthetic text-line images respectively.
Finally, this thesis provides details on various tasks that have been performed for the development
of Amharic OCR. As per our empirical analysis, the majority of the errors are due to poor annotation
of the dataset. As future work, the methods proposed in this thesis should be further investigated
and extended to deal with handwritten and historical Amharic documents.
3D hand pose and shape estimation from a single depth image is a challenging computer vision and graphics problem with many applications such as
human computer interaction and animation of a personalized hand shape in
augmented reality (AR). This problem is challenging due to several factors
for instance high degrees of freedom, view-point variations and varying hand
shapes. Hybrid approaches based on deep learning followed by model fitting
preserve the structure of hand. However, a pre-calibrated hand model limits
the generalization of these approaches. To address this limitation, we proposed a novel hybrid algorithm for simultaneous estimation of 3D hand pose
and bone-lengths of a hand model which allows training on datasets that contain varying hand shapes. On the other hand, direct joint regression methods
achieve high accuracy but they do not incorporate the structure of hand in
the learning process. Therefore, we introduced a novel structure-aware algorithm which learns to estimate 3D hand pose jointly with new structural constraints. These constraints include fingers lengths, distances of joints along
the kinematic chain and fingers inter-distances. Learning these constraints
help to maintain a structural relation between the estimated joint keypoints.
Previous methods addressed the problem of 3D hand pose estimation. We
open a new research topic and proposed the first deep network which jointly
estimates 3D hand shape and pose from a single depth image. Manually annotating real data for shape is laborious and sub-optimal. Hence, we created a
million-scale synthetic dataset with accurate joint annotations and mesh files
of depth maps. However, the performance of this deep network is restricted by
limited representation capacity of the hand model. Therefore, we proposed a
novel regression-based approach in which the 3D dense hand mesh is recovered
from sparse 3D hand pose, and weak-supervision is provided by a depth image synthesizer. The above mentioned approaches regressed 3D hand meshes
from 2D depth images via 2D convolutional neural networks, which leads to
artefacts in the estimations due to perspective distortions in the images. To
overcome this limitation, we proposed a novel voxel-based deep network with
3D convolutions trained in a weakly-supervised manner. Finally, an interesting
application is presented which is in-air signature acquisition and verification
based on deep hand pose estimation. Experiments showed that depth itself is
an important feature, which is sufficient for verification.
In recent years, Augmented Reality has made its way into everyday devices. Most smartphones are AR-enabled, providing applications like pedestrian navigation, Point of Interest highlighting, gaming, and retail. The high-tech industry has been focused on developing smartglasses to present virtual elements directly in front of the viewers’ eyes, allowing more immersive AR experiences. Smartglasses can also be deployed while driving for an enhanced and more safe experience. A 3D registered augmentation of the real world with navigation arrows, lane highlighting, or warnings can decrease the duration of inattentiveness regarding driving due to glancing at other screens. Enabling HMDs’ usage inside cars requires knowing its exact position and orientation (6-DoF pose) in the car. This necessitates sensors either built inside the AR glasses or the car. In a car, the latter option called outside-in tracking is more attractive due to two reasons. First, AR glasses containing different sensor sets exist, hampering finding one single solution for different HMDs. Second, the view from the driver’s perspective combines static interior and dynamic exterior features, complicating finding a reliable set of features. Nowadays, tracking methods utilize Deep Learning for a more generalizable and accurate derivation of the 6-DoF pose. They achieve outstanding results for head and object pose estimation. In this thesis, we present Deep Learning-based in-car 6-DoF AR glasses pose estimation approaches. The goal of the work is an exploration of accurate HMD pose estimation with the help of neural networks. The thesis achieves this by investigating numerous pose estimation techniques. Evaluations on the recorded HMDPose dataset constitute the foundation for this, consisting of infrared images of drivers wearing different HMD models. First, algorithms based on images are derived and evaluated on the dataset. For comparison, we carried out an evaluation on image-based methods considering time information. Further, pose estimation based on point clouds, generated out of infrared images, are analyzed. An investigation of various head pose estimation methods to derive its potential use are conducted. In conclusion, we introduce several highly accurate AR glasses pose estimators. The HMD pose alone achieves better results than the head pose and the combination of the head and HMD. Especially our image-based methods with optional usage of time information can efficiently and accurately regress the AR glasses pose. Our algorithms show excellent estimation results on live data when deployed inside a car, making seamless in-car HMD usage possible in the future.
Faces deliver invaluable information about people. Machine-based perception can be of a great benefit in extracting that underlying information in face images if the problem is properly modeled. Classical image processing algorithms may fail to handle the diverse data available today due to several challenges related to varying capturing locations, and conditions. Advanced machine learning methods and algorithms are now highly beneficial due to the rapid development of powerful hardware, enabling feasible advanced solutions based on data learning and summarization into powerful models. In this thesis, novel solutions are provided to the problems of head orientation estimation and gender prediction. Initially, classical machine learning algorithms were used to address head orientation estimation but were limited by their inability to handle large datasets and poor generalization. To overcome these challenges, a new highly accurate head pose dataset was acquired to tackle the identified problems. Novel trained deep neural networks have been exploited, that use the acquired data and provide novel architectures. The information about head pose is then represented in the network weights, thus, allowing predicting the head orientation angles given a new unseen face. The acquired dataset, named AutoPOSE opens the door for further studies in the field of computer vision and especially, face analysis. The problem of gender prediction has also been explored, but unlike humans who can easily identify gender from a face, computers face difficulties due to facial similarities. Therefore, hand-crafted features are not effective for generalization. To address this, a new deep learning method was developed and evaluated on multiple public datasets, with identified challenges in both still images and videos addressed. Finally, the effect of facial appearance changes due to head orientation variation has been investigated on gender prediction accuracy. A novel orientation-guided feature maps recalibration method is presented, that significantly increased the accuracy of gender prediction.
In conclusion, two problems have been addressed in this thesis, independently and joined together. Existing methods have been enhanced with intelligent pre-processing methods and new approaches have been introduced to tackle existing challenges, that arise from pose, illumination, and occlusion variations. The proposed methods have been extensively evaluated, showing that head orientation and gender prediction can be estimated with high accuracy using machine learning-based methods. Also, the evaluations showed that the use of head orientation information consistently improved the gender prediction accuracy. Scientific contributions have been presented, and the new acquired highly accurate dataset motivates the research community to push the state-of-the-art forward.
DeepKAF: A Knowledge Intensive Framework for Heterogeneous Case-Based Reasoning in Textual Domains
(2021)
Business-relevant domain knowledge can be found in plain text across message exchanges
among customer support tickets, employee message exchanges and other business transactions.
Decoding text-based domain knowledge can be a very demanding task since traditional
methods focus on a comprehensive representation of the business and its relevant paths. Such
a process can be highly complex, time-costly and of high maintenance effort, especially in
environments that change dynamically.
In this thesis, a novel approach is presented for developing hybrid case-based reasoning
(CBR) systems that bring together the benefits of deep learning approaches with CBR advantages.
Deep Knowledge Acquisition Framework (DeepKAF) is a domain-independent
framework that features the usage of deep neural networks and big data technologies to decode
the domain knowledge with the minimum involvement from the domain experts. While
this thesis is focusing more on the textual data because of the availability of the datasets, the
target CBR systems based on DeepKAF are able to deal with heterogeneous data where a
case can be represented by different attribute types and automatically extract the necessary
domain knowledge while keeping the ability to provide an adequate level of explainability.
The main focus within this thesis are automatic knowledge acquisition, building similarity
measures and cases retrieval.
Throughout the progress of this research, several sets of experiments have been conducted
and validated by domain experts. Past textual data produced over around 15 years have
been used for the needs of the conducted experiments. The text produced is a mixture
between English and German texts that were used to describe specific domain problems
with a lot of abbreviations. Based on these, the necessary knowledge repositories were built
and used afterwards in order to evaluate the suggested approach towards effective monitoring
and diagnosis of business workflows. Another public dataset has been used, the CaseLaw
dataset, to validate DeepKAF when dealing with longer text and cases with more attributes.
The CaseLaw dataset represents around 22 million cases from different US states.
Further work motivated by this thesis could investigate how different deep learning models
can be used within the CBR paradigm to solve some of the chronic CBR challenges and be
of benefit to large-scale multi-dimensional enterprises.
Computational simulations run on large supercomputers balance their outputs with the need of the scientist and the capability of the machine. Persistent storage is typically expensive and slow, its peformance grows at a slower rate than the processing power of the machine. This forces scientists to be practical about the size and frequency of the simulation outputs that can be later analyzed to understand the simulation states. Flexibility in the trade-offs of flexibilty and accessibility of the outputs of the simulations are critical the success of scientists using the supercomputers to understand their science. In situ transformations of the simulation state to be persistently stored is the focus of this dissertation.
The extreme size and parallelism of simulations can cause challenges for visualization and data analysis. This is coupled with the need to accept pre partitioned data into the analysis algorithms, which is not always well oriented toward existing software infrastructures. The work in this dissertation is focused on improving current work flows and software to accept data as it is, and efficiently produce smaller, more information rich data, for persistent storage that is easily consumed by end-user scientists. I attack this problem from both a theoretical and practical basis, by managing completely raw data to quantities of information dense visualizations and study methods for managing both the creation and persistence of data products from large scale simulations.
Education is the Achilles heel of successful resuscitation in cardiac arrest. Therefore, we aim to contribute to the educational efficiency by providing a novel augmented-reality (AR) guided interactive cardiopulmonary resuscitation (CPR) "trainer". For this trainer, a mixed reality smart glass, Microsoft HoloLens, and a CPR manikin covered with pressure sensors were used. To introduce the CPR procedure to a learner, an application with an intractable virtual teacher model was designed. The teaching scenario consists of the two main parts, theory and practice. In the theoretical part, the virtual teacher provides all information about the CPR procedure. Afterward, the user will be asked to perform the CPR cycles in three different stages. In the first two stages, it is aimed to gain the muscle memory with audio and optical feedback system. In the end, the performance of the participant is evaluated by the virtual teacher.
Der ProLan-X - Sprachreport
(1992)
Bei der Realisierung großer Software-Projekte treten immer wieder Probleme auf, was die
Koordination der Mitarbeiter, die Ausnutzung der vorhandenen Ressourcen und nicht zuletzt die
Qualität der erzeugten Produkte angeht. Um die Vorgänge bei der Produktion von Software
durchschaubarer und verständlicher zu machen, versucht man, diese aus der Sicht von Meta-Modellen zu beschreiben. Dabei fließen die individuellen Rahmenbedingungen einer jeden
Entwicklungsumgebung ein; die vorhandenen Ressourcen werden ebenso modellien wie die
durchzuführenden Tätigkeiten und ihre Abhängigkeiten. Die Beschreibungssprache für den Software-Prozeß ProLan-X dient der (konkreten) Beschreibung der Bestandteile des Meta-Modells MoMo, das ebenfalls in dieser Arbeitsgruppe entwickelt wurde [Schramm]. Die am Projekt beteiligten Personen, Hardware- und Software-Ressourcen und ihre Aufgaben werden in möglichst natürlicher Weise verhaltensorientien beschrieben. Aus dieser Beschreibung kann eine Ablaufumgebung generien werden, die die Durchführung des Projekts unterstützt und protokolliert. Der vorliegende Bericht faßt die Eigenschaften der Sprache ProLan-X zusammen und erläuten ihre Verwendung. Er setzt das MoMo-Modell als bekannt voraus.
Fast Internet content delivery relies on two layers of caches on the request path. Firstly, content delivery networks (CDNs) seek to answer user requests before they traverse slow Internet paths. Secondly, aggregation caches in data centers seek to answer user requests before they traverse slow backend systems. The key challenge in managing these caches is the high variability of object sizes, request patterns, and retrieval latencies. Unfortunately, most existing literature focuses on caching with low (or no) variability in object sizes and ignores the intricacies of data center subsystems.
This thesis seeks to fill this gap with three contributions. First, we design a new caching system, called AdaptSize, that is robust under high object size variability. Second, we derive a method (called Flow-Offline Optimum or FOO) to predict the optimal cache hit ratio under variable object sizes. Third, we design a new caching system, called RobinHood, that exploits variances in retrieval latencies to deliver faster responses to user requests in data centers.
The techniques proposed in this thesis significantly improve the performance of CDN and data center caches. On two production traces from one of the world's largest CDN AdaptSize achieves 30-91% higher hit ratios than widely-used production systems, and 33-46% higher hit ratios than state-of-the-art research systems. Further, AdaptSize reduces the latency by more than 30% at the median, 90-percentile and 99-percentile.
We evaluate the accuracy of our FOO analysis technique on eight different production traces spanning four major Internet companies.
We find that FOO's error is at most 0.3%. Further, FOO reveals that the gap between online policies and OPT is much larger than previously thought: 27% on average, and up to 43% on web application traces.
We evaluate RobinHood with production traces from a major Internet company on a 50-server cluster. We find that RobinHood improves the 99-percentile latency by more than 50% over existing caching systems.
As load imbalances grow, RobinHood's latency improvement can be more than 2x. Further, we show that RobinHood is robust against server failures and adapts to automatic scaling of backend systems.
The results of this thesis demonstrate the power of guiding the design of practical caching policies using mathematical performance models and analysis. These models are general enough to find application in other areas of caching design and future challenges in Internet content delivery.
Embedded systems are becoming more and more important in today’s life in many ways. They can be found in dishwashers, mobile phones, coffee machines, PDAs, etc. Although there is no common definition of what an embedded system is, it can be generally defined as a special-purpose information processing system, containing both: software and hardware. Embedded systems are integrated in a larger systems which interact with environment for achieving a set of predefined tasks or applications. In general, embedded systems are characterized by resources scarcity, among which energy is becoming more and more important (especially the energy consumed by the processor). The energy consumed by an embedded system is strongly influenced by the software running on it (the embedded software). That is why it is crucial to explore the software characteristics that have an influence on the energy consumption, and to understand how this influence could be represented. In order to realize this task, there is a need for the construction of a reliable measurement platform for energy consumption by embedded devices. The target of this work is to design and implement a framework for measuring energy consumption of embedded software. This framework is based on the XScale architecture, a popular Intel platform designed for energy aware applications. The framework has a software repository which contains a number of programs (user-defined) that are supposed to run on the mentioned platform. These program codes are the input of the framework. Automated measurements for energy consumption are performed on all programs for gathering the required information. In the context of this work, a first evaluation of the framework was performed to make an initial check its quality.
This paper describes the design and implementation of a process support system (PROSYT), which is intended to provide guidance in performing business processes and cooperation among people over a local or geographically distributed architecture. In particular, it can be used as a Process-centered Software Engineering Environment (PSEE) to support distributed software development. Our main purpose is to describe how complex applications of this kind can be developed systematically. In particular, how the requirements of high flexibility, reconfigurability, scalability, and efficiency demanded by these applications can be met through appropriate design choices.
Since their invention in the 1980s, behaviour-based systems have become very popular among roboticists. Their component-based nature facilitates the distributed implementation of systems, fosters reuse, and allows for early testing and integration. However, the distributed approach necessitates the interconnection of many components into a network in order to realise complex functionalities. This network is crucial to the correct operation of the robotic system. There are few sound design techniques for behaviour networks, especially if the systems shall realise task sequences. Therefore, the quality of the resulting behaviour-based systems is often highly dependant on the experience of their developers.
This dissertation presents a novel integrated concept for the design and verification of behaviour-based systems that realise task sequences. Part of this concept is a technique for encoding task sequences in behaviour networks. Furthermore, the concept provides guidance to developers of such networks. Based on a thorough analysis of methods for defining sequences, Moore machines have been selected for representing complex tasks. With the help of the structured workflow proposed in this work and the developed accompanying tool support, Moore machines defining task sequences can be transferred automatically into corresponding behaviour networks, resulting in less work for the developer and a lower risk of failure.
Due to the common integration of automatically and manually created behaviour-based components, a formal analysis of the final behaviour network is reasonable. For this purpose, the dissertation at hand presents two verification techniques and justifies the selection of model checking. A novel concept for applying model checking to behaviour-based systems is proposed according to which behaviour networks are modelled as synchronised automata. Based on such automata, properties of behaviour networks that realise task sequences can be verified or falsified. Extensive graphical tool support has been developed in order to assist the developer during the verification process.
Several examples are provided in order to illustrate the soundness of the presented design and verification techniques. The applicability of the integrated overall concept to real-world tasks is demonstrated using the control system of an autonomous bucket excavator. It can be shown that the proposed design concept is suitable for developing complex sophisticated behaviour networks and that the presented verification technique allows for verifying real-world behaviour-based systems.
AbstractOne main purpose for the use of formal description techniques (FDTs) is formal reasoningand verification. This requires a formal calculus and a suitable formal semantics of theFDT. In this paper, we discuss the basic verification requirements for Estelle, and howthey can be supported by existing calculi. This leads us to the redefinition of the stanADdard Estelle semantics using Lamport's temporal logic of actions and Dijkstra's predicatetransformers.
There is a growing trend for ever larger wireless sensor networks (WSNs) consisting of thousands or tens of thousands of sensor nodes (e.g., [91, 79]). We believe this trend will continue and thus scalability plays a crucial role in all protocols and mechanisms for WSNs. Another trend in many modern WSN applications is the time sensitivity to information from sensors to sinks. In particular, WSNs are a central part of the vision of cyber-physical systems and as these are basically closed-loop systems many WSN applications will have to operate under stringent timing requirements. Hence, it is crucial to develop algorithms that minimize the worst-case delay in WSNs. In addition, almost all WSNs consist of battery-powered nodes, and thus energy-efficiency clearly remains another premier goal in order to keep network lifetime high. This dissertation presents and evaluates designs for WSNs using multiple sinks to achieve high lifetime and low delay. Firstly, we investigate random and deterministic node placement strategies for large-scale and time-sensitive WSNs. In particular, we focus on tiling-based deterministic node placement strategies and analyze their effects on coverage, lifetime, and delay performance under both exact placement and stochastically disturbed placement. Next, we present sink placement strategies, which constitutes the main contributions of this dissertation. Static sinks will be placed and mobile sinks will be given a trajectory. A proper sink placement strategy can improve the performance of a WSN significantly. In general, the optimal sink placement with lifetime maximization is an NP-hard problem. The problem is even harder if delay is taken into account. In order to achieve both lifetime and delay goals, we focus on the problem of placing multiple (static) sinks such that the maximum worst-case delay is minimized while keeping the energy consumption as low as possible. Different target networks may need a corresponding sink placement strategy under differing levels of apriori assumptions. Therefore, we first develop an algorithm based on the Genetic Algorithm (GA) paradigm for known sensor nodes' locations. For a network where global information is not feasible we introduce a self-organized sink placement (SOSP) strategy. While GA-based sink placement achieves a near-optimal solution, SOSP provides a good sink placement strategy with a lower communication overhead. How to plan the trajectories of many mobile sinks in very large WSNs in order to simultaneously achieve lifetime and delay goals had not been treated so far in the literature. Therefore, we delve into this difficult problem and propose a heuristic framework using multiple orbits for the sinks' trajectories. The framework is designed based on geometric arguments to achieve both, high lifetime and low delay. In simulations, we compare two different instances of our framework, one conceived based on a load-balancing argument and one based on a distance minimization argument, with a set of different competitors spanning from statically placed sinks to battery-state aware strategies. We find our heuristics outperform the competitors in both, lifetime and delay. Furthermore, and probably even more important, the heuristic, while keeping its good delay and lifetime performance, scales well with an increasing number of sinks. In brief, the goal of this dissertation is to show that placing nodes and sinks in conventional WSNs as well as planning trajectories in mobility enabled WSNs carefully really pays off for large-scale and time-sensitive WSNs.
Im Rahmen der Arbeit werden verschiedene Ansätze im Bereich Design Rationale untersucht und miteinander verglichen. Darauf aufbauend wird ein Konzept entwickelt, wie Design Rationales in dem Projektplanungs- und Abwicklungswerkzeug CoMo-Kit eingesetzt werden können. Die Realisierung wird beschrieben.
The paper shows that characterizing the causal relationship between significant events is an important but non-trivial aspect for understanding the behavior of distributed programs. An introduction to the notion of causality and its relation to logical time is given; some fundamental results concerning the characterization of causality are pre- sented. Recent work on the detection of causal relationships in distributed computations is surveyed. The relative merits and limitations of the different approaches are discussed, and their general feasibility is analyzed.
This thesis focuses on the operation of reliability-constrained routes in wireless ad-hoc networks. A complete communication protocol that is capable of guaranteeing a statistical minimum reliability level would have to support several functionalities: first, routes that are capable of supporting the specified Quality of Service requirement have to be discovered. During operation of discovered routes, the current Quality of Service level has to be monitored continuously. Whenever significant deviations are detected and the required level of Quality of Service is endangered, route maintenance has to ensure continuous operation. All four functionalities, route discovery, route operation, route maintenance and collection and distribution of network status information, will be addressed in this thesis.
In the first part of the thesis, we propose a new approach for Quality-of- Service routing in wireless ad-hoc networks called rmin-routing, with the provision of statistical minimum route reliability as main route selection criterion. To achieve specified minimum route reliabilities, we improve the reliability of individual links by well-directed retransmissions, to be applied during the operation of routes. To select among a set of candidate routes, we define and apply route quality criteria concerning network load.
High-quality information about the network status is essential for the discovery and operation of routes and clusters in wireless ad-hoc networks. This requires permanent observation and assessment of nodes, links, and link metrics, and the exchange of gathered status data. In the second part of the thesis, we present cTEx, a configurable topology explorer for wireless ad-hoc networks that efficiently detects and exchanges high-quality network status information during operation.
In the third part, we propose a decentralized algorithm for the discovery and operation of reliability-constrained routes in wireless ad-hoc networks called dRmin-routing. The algorithm uses locally available network status information about network topology and link properties that is collected proactively in order to discover a preliminary route candidate. This is followed by a distributed, reactive search along this preselected route to remove imprecisions of the locally recorded network status before making a final route selection. During route operation, dRmin-routing monitors routes and performs different kinds of route repair actions to maintain route reliability in order to overcome varying link reliabilities.
Objective: In some surgical specialties, e.g. orthopedics, robots are already used in the operating room for bony milling work. Oto- and otoneurosurgery may also greatly benefit by robotic enhanced precision. Study Design: Experimental study on robotic milling on oak wood and human temporal bone specimen. Methods: A standard industrial robot with a 6 degrees-of-freedom serial kinematics was used with force feedback to proportionally control the robot speed. Different milling modes and characteristic path parameters were evaluated to generate milling paths based on CAD geometry data of a cochlear implant and an implantable hearing system. Results: The best suited strategy proofed to be the spiral horizontal milling mode with the burr held perpendicularly to the temporal bone surface. In order to avoid high grooves, the distance in between paths should equal half the radius of the cutting burr head. Due to the vibration of the robot’s own motors, a rather high oscillation of the standard deviation of forces was encountered. This oscillation dropped drastically to nearly 0 N, when the burr head reached contact with the dura mater due to its damping characteristics. The cutting burr could be moved a long time on the dura without damaging it, because of its rather blunt head. The robot moved the burr very smoothly according to the encountered resistances. Conclusion: This is the first development of an functioning robotic milling procedure for otoneurosurgery with force-based speed control. It is planned to implement ultrasound-based local navigation and to perform robotic mastoidectomy.
This technical report is a compilation of several papers on the task of solving diagnostic problems with the help of topology preserving maps. It first reviews the application of Kohonen's Self- Organizing Feature Map (SOFM) for a technical diagnosis task, namely the fault detection in CNC-Machines with the KoDiag system [RW93], [RW94]. For emergent problems with coding attribute values, we then introduce fuzzy coding, similarity assignment and weight updating schemes for three crucial data types (continuous values, ordered and unordered symbols). These techniques result in a SOFM type network based on user defined local similarities, thus being able to incorporate a priori knowledge about the domain [Rah95].
Die Beweisentwicklungsumgebung Omega-Mkrp soll Mathematiker bei einer ihrer Haupttätigkeiten, nämlich dem Beweisen mathematischer Theoreme unterstützen. Diese Unterstützung muß so komfortabel sein, daß die Beweise mit vertretbarem Aufwand formal durchgeführt werden können und daß die Korrektheit der so erzeugten Beweise durch das System sichergestellt wird. Ein solches System wird sich nur dann wirklich durchsetzen, wenn die rechnergestützte Suche nach formalen Beweisen weniger aufwendig und leichter ist, als ohne das System. Um dies zu erreichen, ergeben sich verschiedene Anforderungen an eine solche Entwicklungsumgebung, die wir im einzelnen beschreiben. Diese betreffen insbesondere die Ausdruckskraft der verwendeten Objektsprache, die Möglichkeit, abstrakt über Beweispläne zu reden, die am Menschen orientierte Präsentation der gefundenen Beweise, aber auch die effiziente Unterstützung beim Füllen von Beweislücken. Das im folgenden vorgestellte Omega-Mkrp-System ist eine Synthese der Ansätze des vollautomatischen, des interaktiven und des planbasierten Beweisens und versucht erstmalig die Ergebnisse dieser drei Forschungsrichtungen in einem System zu vereinigen. Dieser Artikel soll eine Übersicht über unsere Arbeit an diesem System geben.
This dissertation describes the implementation, validation, and troubleshooting of ``Digital Twins'' in assembly processes of thin structures like parts from the automotive and aerospace industry. As requirements in terms of cost, weight, and human (pedestrian) safety are increasing for modern vehicles, thinner materials are used for exterior components. By that, components become softer but less stable which is challenging for the assembly processes and impacts the resulting quality. The most critical quality measures are gap and flushness as these are affecting aesthetics, wind noise, and fuel consumption of the final vehicle. To compensate for geometrical deviations, parts have adjustable mechanical interfaces which are used to tune in gaps and flushness for each individual assembly. For the components being assembled, individual process parameters depending on the geometry of the actual physical part must be defined. This is a challenging task that cannot be solved in a straightforward manner. However, assembly quality can be predicted by setting up individual Finite Element Method (FEM) simulation models for each part being assembled. These simulation models are called Digital Twin (DTs) as they are enriched with measured properties from the actual physical part. By that, precise predictions can be made and optimal assembly parameters for automated processes are derived. The demonstration use case in this dissertation is the assembly process of exterior car components made from sheet metals. For this kind of process, the geometrical deviations of individual components are crucial and have to be considered by the DT. To capture geometrical deviations, 3D-scanning is employed which provides a high-resolution point cloud representation of the actual physical part. This point cloud is processed further to obtain the DT that preserves the measured geometry. This dissertation tackles the following challenges: (a) setting up DTs on different level of details, (b) correctly post-processing 3D-scanned data to remove systematical measurement errors, (c) automatically morphing meshes to derive simulation models from measured point clouds, and (d) troubleshooting DTs with human-in-the-loop approaches. For all approaches, validations are provided that underline applicability and benefits. All methods and results are discussed on a high-level perspective and connections as well as the interplay between methods are elaborated. Each method either improves or extends existing approaches or provides benefits, i.e. higher precision, compared to existing solutions.
As the properties of components have gradually become clearer, attention has started to turn to the architectural issues which govern their interaction and composition. In this paper we identify some of the major architectural questions affecting component-based software develop-ment and describe the predominant architectural dimensions. Of these, the most interesting is the "architecture hierarchy" which we believe is needed to address the "interface vicissitude" problem that arises whenever interaction refinement is explicitly documented within a component-based system. We present a solution to this problem based on the concept of stratified architectures and object metamorphosis Finally, we describe how these concepts may assist in increasing the tailorability of component-based frameworks.
In this chapter, the quantitative numerical simulation of the behavior of deformable linear objects, such as hoses, wires and leaf springs is studied. We first give a short review of the physical approach and the basic solution principle. Then, we give a more detailed description of some key aspects: We introduce a novel approach concerning dynamics based on an algorithm very similar to the one used for (quasi-) static computation. Then, we look at the plastic workpiece deformation, involving a modified computation algorithm and a special representation of the workpiece shape. Then, we give alternative solutions for two key aspects of the algorithm, and investigate the problem of performing the workpiece simulation efficiently, i.e., with desired precision in a short time. In the end, we introduce the inverse modeling problem which must be solved when the gripper trajectory for a given task shall be generated.
Industrial design has a long history. With the introduction of Computer-Aided Engineering, industrial design was revolutionised. Due to the newly found support, the design workflow changed, and with the introduction of virtual prototyping, new challenges arose. These new engineering problems have triggered
new basic research questions in computer science.
In this dissertation, I present a range of methods which support different components of the virtual design cycle, from modifications of a virtual prototype and optimisation of said prototype, to analysis of simulation results.
Starting with a virtual prototype, I support engineers by supplying intuitive discrete normal vectors which can be used to interactively deform the control mesh of a surface. I provide and compare a variety of different normal definitions which have different strengths and weaknesses. The best choice depends on
the specific model and on an engineer’s priorities. Some methods have higher accuracy, whereas other methods are faster.
I further provide an automatic means of surface optimisation in the form of minimising total curvature. This minimisation reduces surface bending, and therefore, it reduces material expenses. The best results can be obtained for analytic surfaces, however, the technique can also be applied to real-world examples.
Moreover, I provide engineers with a curvature-aware technique to optimise mesh quality. This helps to avoid degenerated triangles which can cause numerical issues. It can be applied to any component of the virtual design cycle: as a direct modification of the virtual prototype (depending on the surface defini-
tion), during optimisation, or dynamically during simulation.
Finally, I have developed two different particle relaxation techniques that both support two components of the virtual design cycle. The first component for which they can be used is discretisation. To run computer simulations on a model, it has to be discretised. Particle relaxation uses an initial sampling,
and it improves it with the goal of uniform distances or curvature-awareness. The second component for which they can be used is the analysis of simulation results. Flow visualisation is a powerful tool in supporting the analysis of flow fields through the insertion of particles into the flow, and through tracing their movements. The particle seeding is usually uniform, e.g. for an integral surface, one could seed on a square. Integral surfaces undergo strong deformations, and they can have highly varying curvature. Particle relaxation redistributes the seeds on the surface depending on surface properties like local deformation or curvature.
In its rather short history robotic research has come a long way in the half century since it started to exist as a noticeable scientic eld. Due to its roots in engineering, computer science, mathematics, and several other 'classical' scientic branches,a grand diversity of methodologies and approaches existed from the very beginning. Hence, the researchers in this eld are in particular used to adopting ideas that originate in other elds. As a fairly logical consequence of this, scientists tended to biology during the 1970s in order to nd approaches that are ideally adapted to the conditions of our natural environment. Doing so allows for introducing principles to robotics that have already shown their great potential by prevailing in a tough evolutionary selection process for millions of years. The variety of these approaches spans from efficient locomotion, to sensor processing methodologies and all the way to control architectures. Thus, the full spectrum of challenges for autonomous interaction with the surroundings while pursuing a task can be covered by such means. A feature that has proven to be amongst the most challenging to recreate is the human ability of biped locomotion. This is mainly caused by the fact that walking,running and so on are highly complex processes involving the need for energy efficient actuation, sophisticated control architectures and algorithms, and an elaborate mechanical design while at the same time posting restrictions concerning stability and weight. However, it is of special interest since our environment is favoring this specic kind of locomotion and thus promises to open up an enormous potential if mastered. More than the mere scientic interest, it is the fascination of understanding and recreating parts of oneself that drives the ongoing eorts in this area of research. The fact that this is not at all an easy task to tackle is not only caused by the highly dynamical processes but also has its roots in the challenging design process. That is because it cannot be limited to just one aspect like e.g. the control architecture, actuation, sensors, or mechanical design alone. Each aspect has to be incorporated into a sound general concept in order to allow for a successful outcome in the end. Since control is in this context inseparably coupled with the mechanics of the system, both has to be dealt with here.
In a networked system, the communication system is indispensable but often the weakest link w.r.t. performance and reliability. This, particularly, holds for wireless communication systems, where the error- and interference-prone medium and the character of network topologies implicate special challenges. However, there are many scenarios of wireless networks, in which a certain quality-of-service has to be provided despite these conditions. In this regard, distributed real-time systems, whose realization by wireless multi-hop networks becomes increasingly popular, are a particular challenge. For such systems, it is of crucial importance that communication protocols are deterministic and come with the required amount of efficiency and predictability, while additionally considering scarce hardware resources that are a major limiting factor of wireless sensor nodes. This, in turn, does not only place demands on the behavior of a protocol but also on its implementation, which has to comply with timing and resource constraints.
The first part of this thesis presents a deterministic protocol for wireless multi-hop networks with time-critical behavior. The protocol is referred to as Arbitrating and Cooperative Transfer Protocol (ACTP), and is an instance of a binary countdown protocol. It enables the reliable transfer of bit sequences of adjustable length and deterministically resolves contest among nodes based on a flexible priority assignment, with constant delays, and within configurable arbitration radii. The protocol's key requirement is the collision-resistant encoding of bits, which is achieved by the incorporation of black bursts. Besides revisiting black bursts and proposing measures to optimize their detection, robustness, and implementation on wireless sensor nodes, the first part of this thesis presents the mode of operation and time behavior of ACTP. In addition, possible applications of ACTP are illustrated, presenting solutions to well-known problems of distributed systems like leader election and data dissemination. Furthermore, results of experimental evaluations with customary wireless transceivers are outlined to provide evidence of the protocol's implementability and benefits.
In the second part of this thesis, the focus is shifted from concrete deterministic protocols to their model-driven development with the Specification and Description Language (SDL). Though SDL is well-established in the domain of telecommunication and distributed systems, the predictability of its implementations is often insufficient as previous projects have shown. To increase this predictability and to improve SDL's applicability to time-critical systems, real-time tasks, an approved concept in the design of real-time systems, are transferred to SDL and extended to cover node-spanning system tasks. In this regard, a priority-based execution and suspension model is introduced in SDL, which enables task-specific priority assignments in the SDL specification that are orthogonal to the static structure of SDL systems and control transition execution orders on design as well as on implementation level. Both the formal incorporation of real-time tasks into SDL and their implementation in a novel scheduling strategy are discussed in this context. By means of evaluations on wireless sensor nodes, evidence is provided that these extensions reduce worst-case execution times substantially, and improve the predictability of SDL implementations and the language's applicability to real-time systems.
In this paper we show that distributing the theorem proving task to several experts is a promising idea. We describe the team work method which allows the experts to compete for a while and then to cooperate. In the cooperation phase the best results derived in the competition phase are collected and the less important results are forgotten. We describe some useful experts and explain in detail how they work together. We establish fairness criteria and so prove the distributed system to be both, complete and correct. We have implementedour system and show by non-trivial examples that drastical time speed-ups are possible for a cooperating team of experts compared to the time needed by the best expert in the team.
The IEEE 802.11 networks have a tremendous growth in the last years, but also now there is a rapid development of the wireless LAN technologies. High transmission rates, simple deployment and especially low costs make this network technology an efficient and cheap way to get access to the Internet. Fon is the world-wide greatest WIFI community and in January 2007 this community offers more than 11.000 access points in Germany and nearly 55.000 all over the world. However, this technology has also his shady sides. For example, it is possible for everyone to receive data from the wireless medium. So a protection against this open data traffic is a encryption mechanism called Wired Equivalent Privacy (WEP). The tragic end of theWired Equivalent Privacy (WEP) and the simplicity of various Denial-of-Service (DoS) attacks on the wireless medium have resulted in giving up the security at the logical-link layer and shifting it to upper layers (or in the best case leaving it within virtual private networks (VPNs)). Nevertheless, there is an enormous growth in using public access to the Internet via HotSpots in cafés, libraries, schools or at airports, train stops etc. Therefore, it is important for the Wireless Internet Service Provider (WISP) to make sure that anyone with a usual wireless device can connect to their access points. Offering this service to anybody makes giving a sufficient level of security very difficult. On the one hand it should be easy for everyone to use this access, on the other hand there is, in most cases, no security. A businessman is not very pleased about phishing his account data for a great enterprise or for his online office like the KIS at the University of Technology in Kaiserslautern. In most cases the WISPs use a simple web based authentication mechanism. By connecting to the WISPs services, the user is redirected to a webpage requesting his login data or credit card information. Therefore the user only needs a wireless LAN device and a webbrowser to authenticate. An attacker could sniff on the wireless medium to phish delicate data from a legal connected user or use DoS attacks as initial point for various other attacks. In most cases, this can be done with no or only small effort. On the other side, in some cases, the WISP has to do a hard reset on his wireless devices after a DoS attack. Therefore an analysis of access points is done in this work. So, the first part is to show how "‘new"’ access points react to flooding attacks and what mechanisms are used to protect them. The second part implements an attack using an anomaly of some access points that are discovered in the first part. And the last chapter deals with some information about using an Intrusion Detection System (IDS) to protect the devices against such attacks.
Dual-Pivot Quicksort and Beyond: Analysis of Multiway Partitioning and Its Practical Potential
(2016)
Multiway Quicksort, i.e., partitioning the input in one step around several pivots, has received much attention since Java 7’s runtime library uses a new dual-pivot method that outperforms by far the old Quicksort implementation. The success of dual-pivot Quicksort is most likely due to more efficient usage of the memory hierarchy, which gives reason to believe that further improvements are possible with multiway Quicksort.
In this dissertation, I conduct a mathematical average-case analysis of multiway Quicksort including the important optimization to choose pivots from a sample of the input. I propose a parametric template algorithm that covers all practically relevant partitioning methods as special cases, and analyze this method in full generality. This allows me to analytically investigate in depth what effect the parameters of the generic Quicksort have on its performance. To model the memory-hierarchy costs, I also analyze the expected number of scanned elements, a measure for the amount of data transferred from memory that is known to also approximate the number of cache misses very well. The analysis unifies previous analyses of particular Quicksort variants under particular cost measures in one generic framework.
A main result is that multiway partitioning can reduce the number of scanned elements significantly, while it does not save many key comparisons; this explains why the earlier studies of multiway Quicksort did not find it promising. A highlight of this dissertation is the extension of the analysis to inputs with equal keys. I give the first analysis of Quicksort with pivot sampling and multiway partitioning on an input model with equal keys.
Dynamic Lambda Calculus
(1999)
The goal of this paper is to lay a logical foundation for discourse theories by providing analgebraic foundation of compositional formalisms for discourse semantics as an analogon tothe simply typed (lambda)-calculus. Just as that can be specialized to type theory by simply providinga special type for truth values and postulating the quantifiers and connectives as constantswith fixed semantics, the proposed dynamic (lambda)-calculus DLC can be specialized to (lambda)-DRT byessentially the same measures, yielding a much more principled and modular treatment of(lambda)-DRT than before; DLC is also expected to eventually provide a conceptually simple basisfor studying higher-order unification for compositional discourse theories.Over the past few years, there have been a series of attempts [Zee89, GS90, EK95, Mus96,KKP96, Kus96] to combine the Montagovian type theoretic framework [Mon74] with dynamicapproaches, such as DRT [Kam81]. The motivation for these developments is to obtain a generallogical framework for discourse semantics that combines compositionality and dynamic binding.Let us look at an example of compositional semantics construction in (lambda)-DRT which is one ofthe above formalisms [KKP96, Kus96]. By the use of fi-reduction we arrive at a first-order DRTrepresentation of the sentence A i man sleeps. (i denoting an index for anaphoric binding.)
Der Bereich der Workflow-Management-Systeme (WFMS - z.B. [Jab95ab]) wird in jüngerer Zeit in verschiedenen Bereichen der Informatik genauer erforscht. Ziel der Bemu"hungen ist es, die besonderen Anforderungen , die WFMS an Rechner- und Programmsysteme stellen, zu ermitteln und zu befriedigen. In dieser Arbeit untersuchen wir Aspekte des Umplanens ("Replanning" bzw. "Remodeling") während der Abarbeitung eines Workflows. Sie entstand im Rahmen des Projektes CoMo-Kit, im Rahmen dessen Methoden und Werkzeuge entwickelt werden, die die Planung und das Management komplexer Arbeitsabläufe, insbesondere im Entwurfsbereich, unterstützen. Der CoMo-Kit wird seit 1989 am Lehrstuhl für Expertensysteme der Universität Kaiserslautern unter der Leitung von Prof. Dr. M.M. Richter entwickelt.
Editorial
(2020)
Editorial
(2020)
Editorial
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Editorial
(2021)
As the usage of concurrency in software has gained importance in the last years, and is still rising, new types of defects increasingly appeared in software. One of the most prominent and critical types of such new defect types are data races. Although research resulted in an increased effectiveness of dynamic quality assurance regarding data races, the efficiency in the quality assurance process still is a factor preventing widespread practical application. First, dynamic quality assurance techniques used for the detection of data races are inefficient. Too much effort is needed for conducting dynamic quality assurance. Second, dynamic quality assurance techniques used for the analysis of reported data races are inefficient. Too much effort is needed for analyzing reported data races and identifying issues in the source code.
The goal of this thesis is to enable efficiency improvements in the process of quality assurance for data races by: (1) analyzing the representation of the dynamic behavior of a system under test. The results are used to focus instrumentation of this system, resulting in a lower runtime overhead during test execution compared to a full instrumentation of this system. (2) Analyzing characteristics and preprocessing of reported data races. The results of the preprocessing are then provided to developers and quality assurance personnel, enabling an analysis and debugging process, which is more efficient than traditional analysis of data race reports. Besides dynamic data race detection, which is complemented by the solution, all steps in the process of dynamic quality assurance for data races are discussed in this thesis.
The solution for analyzing UML Activities for nodes possibly executing in parallel to other nodes or themselves is based on a formal foundation using graph theory. A major problem that has been solved in this thesis was the handling of cycles within UML Activities. This thesis provides a dynamic limit for the number of cycle traversals, based on the elements of each UML Activity to be analyzed and their semantics. Formal proofs are provided with regard to the creation of directed acyclic graphs and with regard to their analysis concerning the identification of elements that may be executed in parallel to other elements. Based on an examination of the characteristics of data races and data race reports, the results of dynamic data race detection are preprocessed and the outcome of this preprocessing is presented to users for further analysis.
This thesis further provides an exemplary application of the solution idea, of the results of analyzing UML Activities, and an exemplary examination of the efficiency improvement of the dynamic data race detection, which showed a reduction in the runtime overhead of 44% when using the focused instrumentation compared to full instrumentation. Finally, a controlled experiment has been set up and conducted to examine the effects of the preprocessing of reported data races on the efficiency of analyzing data race reports. The results show that the solution presented in this thesis enables efficiency improvements in the analysis of data race reports between 190% and 660% compared to using traditional approaches.
Finally, opportunities for future work are shown, which may enable a broader usage of the results of this thesis and further improvements in the efficiency of quality assurance for data races.
Visualization of large data sets, especially on small machines, requires advanced techniques in image processing and image generation. Our hybrid raytracer is capable of rendering volumetric and geometric data simultaneously, without loss of accuracy due to data conversion. Compound data sets, consisting of several types of data, are called "hybrid data sets". There is only one rendering pipeline to obtain loss-less and efficient visualization of hybrid data. Algorithms apply to both types of data. Optical material properties are stored in the same data base for both volumetric and geometric objects, and anti-aliasing methods appeal to both data types. Stereoscopic display routines have been added to obtain true three-dimensional visualization on various media, and animation features allow generation of recordable 3-D sequences.
The \(L_2\)-discrepancy is a quantitative measure of precision for multivariate quadrature rules. It can be computed explicitly. Previously known algorithms needed \(O(m^2\)) operations, where \(m\) is the number of nodes. In this paper we present algorithms which require
\(O(m(log m)^d)\) operations.
As opposed to Monte Carlo integration the quasi-Monte Carlo method does not allow for an (consistent) error estimate from the samples used for the integral approximation. In addition the deterministic error bound of quasi-Monte Carlo integration is not accessible in the setting of computer graphics, since usually the integrands are of unbounded variation. The structure of the high dimensional functionals to be computed for photorealistic image synthesis implies the application of the randomized quasi-Monte Carlo method. Thus we can exploit low discrepancy sampling and at the same time we can estimate the variance. The resulting technique is much more efficient than previous bidirectional path tracing algorithms.
We present an algorithm for determining quadrature rules for computing the direct illumination of predominantly diffuse objects by high dynamic range images. The new method precisely reproduces fine shadow detail, is much more efficient as compared to Monte Carlo integration, and does not require any manual intervention.
The photon map provides a powerful tool for approximating the irradiance in global illumination computations independent from geometry. By presenting new importance sampling techniques, we dramatically improve the memory footprint of the photon map, simplify the caustic generation, and allow for a much faster sampling of direct illumination in complicated models as they arise in a production environment.
Image synthesis often requires the Monte Carlo estimation of integrals. Based on a generalized concept of stratification we present an efficient sampling scheme that consistently outperforms previous techniques. This is achieved by assembling sampling patterns that are stratified in the sense of jittered sampling and N-rooks sampling at the same time. The faster convergence and improved anti-aliasing are demonstrated by numerical experiments.
Recently, the use of abstraction in case-based reasoning (CBR) is getting more and more popular. The basic idea is to supply a CBR system with cases at many different levels of abstraction. When a new problem must be solved, one (or several) 'appropriate' concrete or abstract case are retrieved from the case base and the solution that the case contains is reused to derive a solution for the current problem, e.g. by filling in the details that a retrieved case at some higher level of abstraction does not contain. A major problem that occurs when using this approach is, that for a given new problem, usually several cases, e.g., from different levels of abstraction could be reused to solve the new problem. Choosing a wrong abstract case can slow down the problem solving process or even prevents the problem from being solved.
In dieser Arbeit wird eine Kombinationsmöglichkeit von fallbasiertem und induktivem Schliessen, basierend auf k-d- und Entscheidungsbäumen, entwickelt. Dabei wurde versucht, die Vorteile des induktiven Mechanismus, wie z. B. die sehr effiziente Klassifiz ierung und automatische Generierung, in den fallbasierten Mechanismus zu integrieren. Die Aufgabe zerfällt dabei in zwei Teilaufgaben, die im folgenden zusammengefasst werden.
Diese Arbeit beschäftigt sich mit einer Möglichkeit zur Effizienzverbesserung, wobei das SNLP-basierte Planungssystem CAPlan verwendet wird. Dabei werden neue, zu lösende Probleme einer Vorverarbeitung unterzogen. Dort werden bestimmte Eigenschaften ermittelt, ohne jedoch das Problem zu lösen. Anschliessend wird dem Planungssystem das neue Problem mit dem Zusatzwissen in Form der analysierten Eigenschaften übergeben. Das Planungssystem verwendet das Wissen, um effizienter eine Lösung zu finden.
Diese Arbeit skizziert einen allgemeinen Ansatz zur Montage deformierbarer linearer Werkstücke (wie Kabel, Drähte, Schläuche, Blattfedern) mit Industrierobotern. Hierzu werden insbesondere die folgenden zwei Aspekte betrachtetet. Erstens die zuverlässige Ausführung der Montage unter Berücksichtigung der Werkstückdeformation und anderer Unsicherheiten, zweitens die numerische Simulation des Werkstückverhaltens. Zur robusten Ausführung der Montage wird das aus der Montage starrer Werkstücke bekannte Konzept der Manipulation-Skills auf deformierbare Werkstücke übertragen. Bei der numerischen Simulation wird insbesondere die Bestimmung der Greifertrajektorie bei gegebener Aufgabenstellung betrachtet.
Im Rahmen des Sonderforschungsbereichs SFB314, Projekt X9 "Lernen und Analogie in technischen Expertensystemen", wurde die Verwendbarkeit von Techniken des fallbasierten Schliessens in wissens- basierten Systemen untersucht. Als prototypische Anwendungsdomäne wurde die Arbeitsplanerstellung rotationssymmetrischer Werkstücke gewählt. Im vorliegenden Beitrag wird ein Modell der Arbeits- planerstellung unter Berücksichtigung der verschiedenen, bisher als unabhängig behandelten Planungsmethoden beschrieben. Auf der Basis einer modelbasierte Wissensakquistion aus in Unternehmen verfügbaren Arbeitsplänen wird ein Ausschnitt der Arbeitsplanerstellung, die Aufspannplanung, detailliert. Die Anwendbarkeit wurde durch eine prototypische Realisierung nachgewiesen.
In dieser Arbeit wird ein fallbasiertes System entwickelt, das Angaben über existiertende fallbasierte Anwendungen und Werkzeuge verwaltet. Mit diesem System kann ein Entwickler von fallbasierten Systemen sich einen Überblick über den Stand der Technik verschaffen und vor allem Informationen über Systeme erhalten, die dem System, das er selbst entwickeln will, ähnlich sind.
Selbstorganisation ist eine interessante und vielversprechende Möglichkeit, um die Komplexität verteilter Systeme beherrschbar zu machen. In diesem Beitrag schlagen wir ein leistungsfähiges Rechnersystem auf Basis von rekonfigurierbarer Hardware vor, welches aufgrund seiner Flexibilität in vielen Bereichen eingesetzt werden kann. Es wird die geplante Systemarchitektur und Systemsoftware beschrieben und ein intelligentes, verteiltes Kamerasystem vorgestellt, welches wir als Anwendung mit dem vorgeschlagenen System realisieren wollen, um Selbstorganisation in verteilten Systemen näher zu untersuchen.
Die systematische Verbesserung von Techniken zur Entwicklung und Betreuung von Software setzt eine explizite Darstellung der in einem Projekt ablaufenden Vorgnge (Prozesse) voraus. Diese Darstellungen (Prozemodelle) werden durch Software- Prozemodellierung gewonnen. Eine Sprache zur Beschreibung solcher Modelle ist MVP-L. Verschiedene Standard-Prozemodelle existieren bereits. Bisher gibt es jedoch kaum dokumentierte Software-Entwicklungsprozesse, die speziell fr die Entwicklung reaktiver Systeme entworfen worden sind, d. h. auf die besonderen Anfordernisse bei der Entwicklung reaktiver Systeme zugeschnitten sind. Auch ist bisher nur wenig Erfahrung dokumentiert, fr welche Art von Projektkontexten diese Prozesse gltig sind. Eine Software- Entwicklungsmethode, die - mit Einschrnkungen - zur Entwicklung reaktiver Systeme geeignet ist, ist SOMT (SDL-oriented Object Modeling Technique). Dieser Bericht beschreibt die erfahrungsbasierte Modellierung der Software-Entwicklungsprozesse von SOMT mit MVP-L. Zunchst werden inhaltliche Grundlagen der Software-Entwicklungsmethode SOMT beschrieben. Insbesondere wird auf die eingesetzten Techniken und deren Kombination eingegangen. Anschlieend werden mgliche Projektkontexte charakterisiert, in denen das SOMT-Modell im Sinne eines Erfahrungselements Gltigkeit hat. Darauf werden der Modellierungsvorgang sowie hierbei gemachte Erfahrungen dokumentiert. Eine vollstndige Darstellung des Modells in grafischer MVP-L-Notation befindet sich im Anhang. Die Darstellung des Modells in textueller Notation kann der SFB-Erfahrungsdatenbank entnommen werden.
In diesem Beitrag wird gezeigt, wie mit Hilfe von Knowledge Engineering Techniken eine komplexe Domäne, die Entwicklung von Bebauungsplänen, modelliert werden kann. Dabei wird insbesondere auf notwendige Erweiterungen bekannter Ansätze eingegangen, die sich aus einer praxisbezogenen Entwurfsdomäne ergeben. Der beschriebene Ansatz unterstützt die Koordination mehrerer Agenten durch die Verwaltung von Abhängigkeiten. Das beschriebene Projekt "Intelligenter Bebauungsplan" integriert GIS/CAD, Hypertext und Expertensystemtechnologie. Die Strukturierung der benötigten Informationen als Hypertext wurde von den beteiligten Stadtplanern gewünscht und ist eine natürliche Repräsentation für Gesetzestexte (und Kommentare), da sie ohnehin viele Querverweise enthalten.
Hadoop ist ein beliebtes Framework für verteilte Berechnungen über große
Datenmengen (Big Data) mittels MapReduce. Hadoop zu verwenden ist einfach: Der
Entwickler definiert die Eingabedatenquelle und implementiert die beiden
Methoden Map und Reduce. Über die verteilte Berechnung und Fehlerbehandlung muss
er sich dabei keine Gedanken machen, das erledigt das Hadoop-Framework.
Allerdings kann die Analyse von Big Data sehr lange dauern und da sich die
Eingabedaten jede Sekunde ändern, ist es vielleicht nicht immer die beste
Idee, die vollständige Berechnung jedes Mal aufs Neue auf die kompletten
Eingabedaten anzuwenden. Es wäre geschickter, sich das Ergebnis der
vorherigen Berechnung zu betrachten und nur die Deltas zu analysieren, also
Daten, die seit der letzten Berechnung hinzugefügt oder gelöscht wurden. In dem Gebiet der
selbstwartbaren materialisierten Sichten in relationalen Datenbanksystemen gibt
es bereits mehrere Ansätze, die sich mit der Lösung dieses Problems
beschäftigen. Eine Strategie liest nur die Deltas und inkrementiert oder
dekrementiert die Ergebnisse der vorherigen Berechnung. Allerdings ist diese
Inkrement-Operation sehr teuer, deshalb ist es manchmal besser, das komplette
alte Ergebnis zu lesen und es mit den Deltas der Eingabedaten zu kombinieren.
In dieser Masterarbeit wird ein neues Framework namens Marimba vorgestellt,
welches sich genau um diese Probleme der inkrementellen Berechnung kümmert. Einen
Map\-Re\-duce-Job in Marimba zu schreiben ist genau so einfach wie einen Hadoop-Job.
Allerdings werden hier keine Mapper- und Reducer-Klasse implementiert, sondern
eine Translator- und Serializer-Klasse. Der Translator ähnelt dem Mapper: Er
bestimmt, wie die Eingabedaten gelesen und daraus Zwischenwerte berechnet
werden. Der Serializer erzeugt die Ausgabe des Jobs. Wie diese Ausgabe berechnet
wird, gibt der Benutzer durch Implementierung einiger Methoden an, um Werte zu
aggregieren und invertieren.
Vier MapReduce-Jobs, darunter auch das Paradebeispiel für MapReduce WordCount,
wurden im Marimba-Framework implementiert. Das Entwickeln von inkrementellen
Map-Reduce-Jobs ist mit dem Framework extrem einfach geworden. Außerdem konnte
mit Performanztests gezeigt werden, dass die inkrementelle Berechnung deutlich
schneller ist als eine vollständige Neuberechnung.
Ein weiterer unter den vier implementierten Jobs berechnet
Wortauftrittswahrscheinlichkeiten in geschriebenen Sätzen. Dies kann
beispielsweise für Spracherkennung verwendet werden. Wenn ein Wort in einer
gesprochenen SMS nicht richtig verstanden wurde, hilft der Algorithmus zu raten,
welches Wort am wahrscheinlichsten an einer bestimmten Stelle stehen könnte,
abhängig von den vorherigen Wörtern im Satz. Damit dieser Algorithmus auch
brauchbare Ergebnisse liefert, ist die Menge und die Qualität der Eingabedaten
wichtig. Durchaus brauchbare Ergebnisse wurden durch die Verarbeitung von
Millionen von Twitter-Feeds, die deutsche Twitter-Nutzer in den letzten Monaten
geschrieben haben, erreicht.
Ein maßgeschneidertes Kommunikationssystem für eine mobile Applikation mit Dienstgüteanforderungen
(2004)
In diesem Beitrag wird die Maßschneiderung eines Ad-Hoc-Kommunikationssystems zur Fernsteuerung eines Luftschiffs über WLAN vorgestellt. Dabei steht die Dienstunterstützung bei der Übertragung mehrerer Datenströme im Vordergrund. Es werden verschiedene Dienstgütemechanismen erklärt und deren Entwicklung und Integration in ein Kommunikationsprotokoll mit Hilfe eines komponentenbasierten Ansatzes genauer erläutert.
Software stellt ein komplexes Werkzeug dar, das durch seine umfassenden Möglichkeiten die moderne Gesellschaft entscheidend geprägt hat. Daraus ergibt sich eine Abhängigkeit von Funktion und Fehlfunktion der Software, die eine an den funktionalen Anforderungen orientierte Entwicklung und Qualitätssicherung der Software notwendig macht. Die vorliegende Arbeit schafft durch Formalisierung und Systematisierung der Verfahren im funktionsorientierten Test eine fundierte Basis für eine Hinwendung zu den funktionsorientierten Techniken in Softwareentwicklung und –qualitätssicherung. Hierzu wird in der Arbeit zunächst ein formales Modell für das Vorgehen im dynamischen Test beschrieben, das sich an der Begriffsbildung der Literatur und dem Verständnis der Praxis orientiert. Das Modell beruht auf wenigen zentralen Annahmen, eignet sich für formale Untersuchungen und Nachweise und ist wegen seiner sehr allgemein gehaltenen Definitionen breit anwendbar und einfach erweiterbar. Auf dieser Basis werden Vorgehen und Verfahren zum funktionsorientierten Test analysiert. Zunächst wird dazu das Vorgehen im funktionsorientierten Test im Rahmen des Modells dargestellt. Darauf aufbauend werden zentrale Verfahren des funktionsorientierten Tests analysiert, die zum Gegenstand die systematische Prüfung der Umsetzung von weitgehend informal beschriebenen Anforderungen in einem Softwareprodukt haben. Betrachtet werden Verfahren der funktionalen Partitionierung, der funktionalen Äquivalenzklassenanalyse und Grenzwertbildung, Verfahren zur Prüfung von kausalen Zusammenhängen zwischen Ursachen und Wirkungen, Verfahren zur Prüfung von graphisch spezifizierter Funktionalität in Syntaxdiagrammen, Aktivitätsdiagrammen, Sequenz- und Kollaborationsdiagrammen und Petrinetzen, Verfahren zum Test zustandsbasierter Systeme sowie Ansätze einer funktionalen Dekomposition. Die Analyse und Diskussion der bekannten Verfahren im formalisierten Rahmenwerk führt zu zahlreichen Ergebnissen und Verfahrensergänzungen. So zeigt sich, dass in den klassischen, informalen Beschreibungen häufig Unklarheiten bestehen. Diese werden hier adressiert und durch Angabe von Kriterien präzisiert, Optimierungsmöglichkeiten werden aufgezeigt. Darüber hinaus wird an der einheitlichen formalen Darstellung der in der Literatur meist separat betrachteten Verfahren deutlich, welche Vergleichbarkeit zwischen den Verfahren besteht, welche Verfahrenskombinationen sinnvoll sind und wie durch ein kombiniert funktions- und strukturorientiertes Vorgehen eine hohe Aussagekraft in der analytischen Qualitätssicherung erreicht werden kann. Bei der Formulierung der Verfahren im Rahmen des Modells wird herausgearbeitet, wo zur Verfahrensdurchführung die kreative Leistung des Testers notwendig ist und welche Anteile formalisiert und damit automatisiert unterstützt werden können. Diese Betrachtungen bilden die Grundlage für die Skizzierung einer integrierten Entwicklungsumgebung, in der ein funktionsorientiertes Vorgehen in Entwicklung und Qualitätssicherung umgesetzt wird: Hier helfen funktionsorientierte Beschreibungsformen bei der Angabe der Spezifikation, ihrer Verfeinerung und ihrer Vervollständigung, sie unterstützen die Entwicklung durch Modellbildung, sie liefern die Basis für eine funktionsorientierte Testdatenselektion mit Adäquatheitsprüfung, sie können bei geeigneter Interpretierbarkeit über den Datenbereichen zur automatisierten Testfallgenerierung genutzt werden und unterstützen als suboptimale Testorakel eine automatisierte Auswertung des dynamischen Tests. Diese Skizze zeigt die praktische Umsetzbarkeit der vorwiegend theoretischen Ergebnisse dieser Arbeit und setzt einen Impuls für ein verstärktes Aufgreifen funktionsorientierter Techniken in Wissenschaft und Praxis.
Ein verhaltensorientierter Ansatz zum flächendeckenden Fahren in a priori unbekannter Umgebung
(1998)
In diesem Aufsatz wird ein Verfahren zum flächendeckenden Fahren in zu- nächst unbekannter Umgebung beschrieben, wie es z.B. für Reinigungsanwen- dungen im Heimbereich benötigt wird. Parallel zur Durchführung der Reini- gungsaufgabe wird dabei die Umgebung exploriert und kartiert. Der verhaltensorientierte Ansatz ermöglicht eine robuste, zielgerichtete und dennoch ressourcenschonende Implementierung und gestattet es, einzelne Ver- haltensweisen leicht durch verbesserte oder auch speziell erlernte Versionen auszutauschen. Das vorgestellte Verfahren wurde simulativ getestet und wird in Kürze auf einem realen Roboter erprobt.
In diesem Aufsatz wird die Arbeitsweise eines Werkzeuges dargestellt, mit dessen Hilfedie Analyse von Feature-Interaktionen in Intelligenten (Telefon-)Netzwerken unterstütztwird. Dieses Werkzeug basiert auf einem von uns entwickelten formalen Lösungsansatz, deraus einem geeigneten Spezifikationsstil, aus einem formalen Kriterium zur Erkennung vonFeature-Interaktionen und aus einer Methode zur Auflösung der erkannten Feature- Interaktionen besteht. Das Werkzeug führt eine statische Analyse von Estelle-Spezifikationendurch und erkennt dabei potientielle Feature-Interaktionen sowie nichtausführbare Transitionen. Darüberhinaus kann es die erkannten nichtausführbaren Transitionen zur Optimierung aus der Spezifikation entfernen. Wir erläutern zunächst kurz den zugrundeliegendenAnsatz und beschreiben danach die Anwendung auf Estelle anhand der Funktionsweisedes Werkzeuges.
Die Bewegungsplanung für Industrieroboter ist eine notwendige Voraussetzung, damit sich autonome Systeme kollisionsfrei durch die Umwelt bewegen können. Die Berücksichtigung von dynamischen Hindernissen zur Laufzeit erfordert allerdings leistungsfähige Algorithmen, zur Lösung dieser Aufgabenstellung in Echtzeit. Eine Möglichkeit zur Beschleunigung der Algorithmen ist der effiziente Einsatz von skalierbarer Parallelverarbeitung. Die softwaretechnische Umsetzung kann aber nur dann erfolgreich sein, wenn ein Parallelrechner zur Verfügung steht, der einen hohen Datendurchsatz bei geringer Latenzzeit bietet. Darüber hinaus muß dieser Parallelrechner unter vertretbarem Aufwand bedienbar sein und ein gutes Preisleistungsverhältnis aufweisen, damit die Parallelverarbeitung verstärkt in der Industrie zum Einsatz kommt. In diesem Artikel wird ein Workstation-Cluster auf der Basis von neun Standard- PCs vorgestellt, die über eine spezielle Kommunikationskarte miteinander vernetzt sind. In den einzelnen Abschnitten werden die gesammelten Erfahrungen bei der Inbetriebnahme, Systemadministration und Anwendung geschildert. Als Beispiel für eine Anwendung auf diesem Cluster wird ein paralleler Bewegungsplaner für Industrieroboter beschrieben.
In dieser Arbeit beschreiben wir einen Ansatz zur automatischen Synthese zustandsendlicher, reaktiver Systeme, ausgehend von einer rein deklarativen, logischen Spezifikation. Dazu verwenden wir temporal stratifizierte Programme,
das sind spezielle Logik-Programme auf der Grundlage einer linearen, temporalen Aussagenlogik. Die Umgebung eines zu implementierenden Steuerungsprogrammes wird hier durch eine Menge von PROLOG-ähnlichen Programmklauseln beschrieben; zusätzlich wird eine Sicherheitsbedingung angegeben, die in dem System gelten soll. Wir zeigen, wie durch eine solche Spezifikation ein sie implementierender endlicher Automat definiert ist und geben einen Algorithmus zu seiner Berechnung auf der Grundlage einer Fixpunkt-Iteration an.
Beim funktionsorientierten Testen von Steuergeräten im automobilen Bereich ist das Expertenwissen aufgrund der hohen Komplexität der Testfälle unersetzlich. Bei Basistesttechniken wie der Grenzwertanalyse ist die Absicht eines Testfalls implizit durch die Technik gegeben. Beim Expertenwissen wird jedoch zur Zeit zu jedem erstellten Testfall zusätzlich ein Prosatext verfasst um die Testabsicht anzugeben. Diese Prosabeschreibung ist anfällig für Mehrdeutigkeiten, fällt bei jedem Testentwickler unterschiedlich aus und der inhaltliche Bezug zum Testfall ist lose. Ziel der Arbeit ist eine Spezifikationssprache für die Testfallbeschreibung zu entwerfen um die Nachteile der natürlichen Sprache zu minimieren und testablaufspezifische Sprachelemente zu definieren, so dass sie als ein Grundgerüst für einen Testfall verwendet werden kann. Dazu wird aus der Einsatzumgebung (Systemspezifikation, Testimplementierung und Testprozessthemen) Sprachelemente für die Beschreibung abgeleitet und Ansätze für die Überführung der Beschreibung in die Testimplementierung betrachtet. Das Ergebnis ist eine Testfall-Spezifikationssprache, die auf formaler Grundlage basiert und u.a. in eine graphische Sicht überführt werden kann. Ähnlich der UML wird der Mehrwert erst durch eine werkzeugunterstützte Eingabe deutlich: So sind die Testentwickler in der Lage, einheitliche, formale, wieder verwendbare, verständliche Testfälle zu definieren.
Die Entwicklung des Zusammenlebens der Menschen geht immer mehr den Weg zur Informations- und Mediengesellschaft. Nicht zuletzt aufgrund der weltweiten Vernetzung ist es uns in minutenschnelle möglich, fast alle erdenklichen Informationen zu Hause auf den Bildschirm geliefert zu bekommen. Es findet sich so jeder zwar in einer gewissen schützenden Anonymität, aber dennoch einer genauso gewollten, wie erschreckenden Transparenz wieder. Jeder klassifiziert in gewisser Weise Informationen, die er preisgibt etwa in öffentliche, persönliche und vertrauliche Nachrichten. Gerade hier müssen Techniken und Methoden bereitstehen, um in dieser anonymen Transparenz Informationen, die nur für spezielle Empfänger gedacht sind vor unbefugtem Zugriff zu schützen und nur denjenigen zugänglich zu machen, die dazu berechtigt sind. Diesen Wunsch hat nicht nur allgemein die Gesellschaft, sondern im speziellen wird die Entwicklung auf diesem Gebiet gerade von staatlichen und militärischen Einrichtungen gefordert und gefördert. So sind häufig eingesetzte Werkzeuge die Methoden der Kryptologie, aber solange es geheime Nachrichten gibt, wird es Angreifer geben, die versuchen, sich unberechtigten Zugang zu diesen Informationen zu verschaffen. Da die ständig wachsende Leistung von EDV-Anlagen das "Knacken" von Verschlüsselungsmethoden begünstigt, muß zu immer sichereren Chiffrierverfahren übergegangen werden. Dieser Umstand macht das Thema Kryptologie für den Moment hochaktuell und auf lange Sicht zu einem zeitlosen Forschungsgebiet der Mathematik und Informatik.