Efficient solving of structural constraints

  • Authors:

  • Bassem Elkarablieh;Darko Marinov;Sarfraz Khurshid

  • Affiliations:

  • The University of Texas at Austin, Austin, TX, USA;The University of Illinois at Urbana, Urbana, IL, USA;The University of Texas at Austin, Austin, TX, USA

  • Venue:
  • ISSTA '08 Proceedings of the 2008 international symposium on Software testing and analysis
  • Year:
  • 2008

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Abstract

Structural constraint solving is being increasingly used for software reliability tasks such as systematic testing or error recovery. For example, the Korat algorithm provides constraint-based test generation: given a Java predicate that describes desired input constraints and a bound on the input size, Korat systematically searches the bounded input space of the predicate to generate all inputs that satisfy the constraints. As another example, the STARC tool uses a constraint-based search to repair broken data structures. A key issue for these approaches is the efficiency of search. This paper presents a novel approach that significantly improves the efficiency of structural constraint solvers. Specifically, most existing approaches use backtracking through code re-execution to explore their search space. In contrast, our approach performs checkpoint-based backtracking by storing partial program states and performing abstract undo operations. The heart of our approach is a light-weight search that is performed purely through code instrumentation. The experimental results on Korat and STARC for generating and repairing a set of complex data structures show an order to two orders of magnitude speed-up over the traditionally used searches.