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Constraints in Dynamic Symbolic Execution: Bitvectors or Integers?

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Tests and Proofs (TAP 2019)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11823))

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Dynamic symbolic execution is a technique that analyses programs by gathering mathematical constraints along execution paths. To achieve bit-level precision, one must use the theory of bitvectors. However, other theories might achieve higher performance, justifying in some cases the possible loss of precision.

In this paper, we explore the impact of using the theory of integers on the precision and performance of dynamic symbolic execution of C programs. In particular, we compare an implementation of the symbolic executor KLEE using a partial solver based on the theory of integers, with a standard implementation of KLEE using a solver based on the theory of bitvectors, both employing the popular SMT solver Z3. To our surprise, our evaluation on a synthetic sort benchmark, the ECA set of Test-Comp 2019 benchmarks, and GNU Coreutils revealed that for most applications the integer solver did not lead to any loss of precision, but the overall performance difference was rarely significant.

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We would like to thank Yannick Moy for challenging us at the Dagstuhl Seminar 19062 to pursue this direction of research, and Frank Busse and the anonymous reviewers for their valuable feedback. This research was generously sponsored by the UK EPSRC via grant EP/N007166/1 and a PhD studentship.

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Correspondence to Martin Nowack .

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Kapus, T., Nowack, M., Cadar, C. (2019). Constraints in Dynamic Symbolic Execution: Bitvectors or Integers?. In: Beyer, D., Keller, C. (eds) Tests and Proofs. TAP 2019. Lecture Notes in Computer Science(), vol 11823. Springer, Cham.

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