Representations of activities dealing with the development or maintenance of software are called software process models. Process models allow for communication, reasoning, guidance, improvement, and automation. Two approaches for building, instantiating, and managing processes, namely CoMo-Kit and MVP-E, are combined to build a more powerful one. CoMo-Kit is based on AI/KE technology; it was developed for supporting complex design processes and is not specialized to software development processes. MVP-E is a process-sensitive software engineering environment for modeling and analyzing software development processes, and guides software developers. Additionally, it provides services to establish and run measurement programmes in software organizations. Because both approaches were developed completely independently major integration efforts are to be made to combine their both advantages. This paper concentrates on the resulting language concepts and their operationalization necessary for building automated process support.
In this paper we describe a framework for defining and operationalizing conceptual models of distributed knowledge-based systems which extends published approaches by the notion of ,agents" and multiple task decompositions. The main part deals with techniques underlying our distributed interpreter. We show how a client-server-architecture can be implemented which allows prototyping distributed knowledge-based systems. Further we describe our mechanism which manages task interactions and supports dependency-directed backtracking efficiently.
In this paper we present an interpreter which allows to support the validation of conceptual models in early stages of the development. We compare hypermedia and expert system approaches to knowledge processing and show how an integrated approach eases the creation of expert systems. Our knowledge engineering tool CoMo-Kit allows a "smooth" transition from initial protocols via a semi-formal specification based on a typed hypertext up to an running expert system. The interpreter uses the intermediate hypertext representation for the interactive solution of problems. Thereby, tasks are distributed to agents via an local area network. This means that the specification of an expert system can directly be used to solve real world problems. If there exist formal (operational) specifications for subtasks then these are delegated to computers. Therefore, our approach allows to specify and validate distributed, cooperative systems where some subtasks are solved by humans and other subtasks are solved automatically by computers.
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:
This paper describes how knowledge-based techniques can be used to overcome problems of workflow management in engineering applications. Using explicit process and product models as a basis for a workflow interpreter allows to alternate planning and execution steps, resulting in an increased flexibility of project coordination and enactment. To gain the full advantages of this flexibility, change processes have to be supported by the system. These require an improved traceability of decisions and have to be based on dependency management and change notification mechanisms. Our methods and techniques are illustrated by two applications: Urban land-use planning and software process modeling.
In this paper we will present a design model (in the sense of KADS) for the domain of technical diagnosis. Based on this we will describe the fully implemented expert system shell MOLTKE 3.0, which integrates common knowledge acquisition methods with techniques developed in the fields of Model-Based Diagnosis and Machine Learning, especially Case-Based Reasoning.
The paper presents a process-oriented view on knowledge management in software development. We describe requirements on knowledge management systems from a process-oriented perspective, introduce a process modeling language MILOS and its use for knowledge management. Then we explain how a process-oriented knowledge management system can be implemented using advanced but available information technologies.
This paper describes a system that supports softwaredevelopment processes in virtual software corporations. A virtual software corporation consists of a set of enterprisesthat cooperate in projects to fulfill customer needs. Contracts are negotiated in the whole lifecycle of asoftware development project. The negotiations really influence the performance of a company. Therefore, it isuseful to support negotiations and planning decisions with software agents. Our approach integrates software agentapproaches for negotiation support with flexible multiserver workflow engines.