Parallel bounded analysis in code with rich invariants by refinement of field bounds

Authors:
Nicolás Rosner;Juan Galeotti;Santiago Bermúdez;Guido Marucci Blas;Santiago Perez De Rosso;Lucas Pizzagalli;Luciano Zemín;Marcelo F. Frias
Affiliations:
UBA, Argentina;Saarland University, Germany;ITBA, Argentina;ITBA, Argentina;ITBA, Argentina;ITBA, Argentina;ITBA, Argentina;ITBA, Argentina
Venue:
Proceedings of the 2013 International Symposium on Software Testing and Analysis
Year:
2013

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Abstract

In this article we present a novel technique for automated parallel bug-finding based on the sequential analysis tool TACO. TACO is a tool based on SAT-solving for efficient bug-finding in Java code with rich class invariants. It prunes the SAT-solver's search space by introducing precise symmetry-breaking predicates and bounding the relational semantics of Java class fields. The bounds computed by TACO generally include a substantial amount of nondeterminism; its reduction allows us to split the original analysis into disjoint subproblems. We discuss the soundness and completeness of the decomposition. Furthermore, we present experimental results showing that MUCHO-TACO, our tool which implements this technique, yields significant speed-ups over TACO on commodity cluster hardware.