Zilong Wang

• Software is becoming increasingly concurrent: parallelization, decentralization, and reactivity necessitate asynchronous programming in which processes communicate by posting messages/tasks to others’ message/task buffers. Asynchronous programming has been widely used to build fast servers and routers, embedded systems and sensor networks, and is the basis of Web programming using Javascript. Languages such as Erlang and Scala have adopted asynchronous programming as a fundamental concept with which highly scalable and highly reliable distributed systems are built. Asynchronous programs are challenging to implement correctly: the loose coupling between asynchronously executed tasks makes the control and data dependencies difficult to follow. Even subtle design and programming mistakes on the programs have the capability to introduce erroneous or divergent behaviors. As asynchronous programs are typically written to provide a reliable, high-performance infrastructure, there is a critical need for analysis techniques to guarantee their correctness. In this dissertation, I provide scalable verification and testing tools to make asyn- chronous programs more reliable. I show that the combination of counter abstraction and partial order reduction is an effective approach for the verification of asynchronous systems by presenting PROVKEEPER and KUAI, two scalable verifiers for two types of asynchronous systems. I also provide a theoretical result that proves a counter-abstraction based algorithm called expand-enlarge-check, is an asymptotically optimal algorithm for the coverability problem of branching vector addition systems as which many asynchronous programs can be modeled. In addition, I present BBS and LLSPLAT, two testing tools for asynchronous programs that efficiently uncover many subtle memory violation bugs.