Demand-Driven Compositional Symbolic Execution

  • Saswat Anand
  • Patrice Godefroid
  • Nikolai Tillmann
Conference paper

DOI: 10.1007/978-3-540-78800-3_28

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4963)
Cite this paper as:
Anand S., Godefroid P., Tillmann N. (2008) Demand-Driven Compositional Symbolic Execution. In: Ramakrishnan C.R., Rehof J. (eds) Tools and Algorithms for the Construction and Analysis of Systems. TACAS 2008. Lecture Notes in Computer Science, vol 4963. Springer, Berlin, Heidelberg

Abstract

We discuss how to perform symbolic execution of large programs in a manner that is both compositional (hence more scalable) and demand-driven. Compositional symbolic execution means finding feasible interprocedural program paths by composing symbolic executions of feasible intraprocedural paths. By demand-driven, we mean that as few intraprocedural paths as possible are symbolically executed in order to form an interprocedural path leading to a specific target branch or statement of interest (like an assertion). A key originality of this work is that our demand-driven compositional interprocedural symbolic execution is performed entirely using first-order logic formulas solved with an off-the-shelf SMT (Satisfiability-Modulo-Theories) solver – no procedure in-lining or custom algorithm is required for the interprocedural part. This allows a uniform and elegant way of summarizing procedures at various levels of detail and of composing those using logic formulas.

We have implemented a prototype of this novel symbolic execution technique as an extension of Pex, a general automatic testing framework for .NET applications. Preliminary experimental results are encouraging. For instance, our prototype was able to generate tests triggering assertion violations in programs with large numbers of program paths that were beyond the scope of non-compositional test generation.

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Saswat Anand
    • 1
  • Patrice Godefroid
    • 2
  • Nikolai Tillmann
    • 2
  1. 1.Georgia Institute of Technology 
  2. 2.Microsoft Research 

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