Abstract. One of the main challenges of dynamic symbolic executionan automated program analysis technique which has been successfully employed to test a variety of software-is constraint solving. A key decision in the design of a symbolic execution tool is the choice of a constraint solver. While different solvers have different strengths, for most queries, it is not possible to tell in advance which solver will perform better. In this paper, we argue that symbolic execution tools can, and should, make use of multiple constraint solvers. These solvers can be run competitively in parallel, with the symbolic execution engine using the result from the best-performing solver. We present empirical data obtained by running the symbolic execution engine KLEE on a set of real programs, and use it to highlight several important characteristics of the constraint solving queries generated during symbolic execution. In particular, we show the importance of constraint caching and counterexample values on the (relative) performance of KLEE configured to use different SMT solvers. We have implemented multi-solver support in KLEE, using the metaSMT framework, and explored how different state-of-the-art solvers compare on a large set of constraint-solving queries. We also report on our ongoing experience building a parallel portfolio solver in KLEE.

Abstract. We describe and report upon various substantial extensions of the CSP refinement checker FDR including (i) the direct ability to handle real-time processes; (ii) the incorporation of bounded model checking technology; (iii) the development of conservative and highly efficient static analysis algorithms for guaranteeing livelock-freedom; and (iv) the development of automated CEGAR technology.

While developers are aware of the importance of comprehensively testing patches, the large effort involved in coming up with relevant test cases means that such testing rarely happens in practice. Furthermore, even when test cases are written to cover the patch, they often exercise the same behaviour in the old and the new version of the code. In this article, we present a symbolic execution-based technique that is designed to generate test inputs that cover the new program behaviours introduced by a patch. The technique works by executing both the old and the new version in the same symbolic execution instance, with the old version shadowing the new one. During this combined shadow execution, whenever a branch point is reached where the old and the new version diverge, we generate a test input exercising the divergence and comprehensively test the new behaviours of the new version. We evaluate our technique on the Coreutils patches from the CoREBench suite of regression bugs, and show that it is able to generate test inputs that exercise newly added behaviours and expose some of the regression bugs.

In a process algebra with hiding and recursion it is possible to create processes which compute internally without ever communicating with their environment. Such processes are said to diverge or livelock. In this paper we show how it is possible to conservatively classify processes as livelock-free through a static analysis of their syntax. In particular, we present a collection of rules, based on the inductive structure of terms, which guarantee livelock-freedom of the denoted process. This gives rise to an algorithm which conservatively flags processes that can potentially livelock. We illustrate our approach by applying both BDD-based and SAT-based implementations of our algorithm to a range of benchmarks, and show that our technique in general substantially outperforms the model checker FDR whilst exhibiting a low rate of inconclusive results.Comment: 53 pages, 20 figure