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A Comparative Study of Incremental Constraint Solving Approaches in Symbolic Execution

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8855)

Abstract

Constraint solving is a major source of cost in Symbolic Execution (SE). This paper presents a study to assess the importance of some sensible options for solving constraints in SE. The main observation is that stack-based approaches to incremental solving is often much faster compared to cache-based approaches, which are more popular. Considering all 96 C programs from the KLEE benchmark that we analyzed, the median speedup obtained with a (non-optimized) stack-based approach was of 5x. Results suggest that tools should take advantage of incremental solving support from modern SMT solvers and researchers should look for ways to combine stack- and cache-based approaches to reduce execution cost even further. Instructions to reproduce results are available online: http://asa.iti.kit.edu/130_392.php

Keywords

Time Budget Boolean Expression Symbolic Execution Constraint Solver Path Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Karlsruhe Institute of TechnologyGermany
  2. 2.Federal University of PernambucoBrazil

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