Symbolic search-based testing

Authors:
Arthur Baars;Mark Harman;Youssef Hassoun;Kiran Lakhotia;Phil McMinn;Paolo Tonella;Tanja Vos
Affiliations:
Universidad Politécnica de Valencia, Spain;University College London, CREST Centre, U.K.;King's College London, U.K.;University College London, CREST Centre, U.K.;University of Sheffield, U.K.;Fondazione Bruno Kessler, Trento, Italy;Universidad Politécnica de Valencia, Spain
Venue:
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
Year:
2011

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Abstract

We present an algorithm for constructing fitness functions that improve the efficiency of search-based testing when trying to generate branch adequate test data. The algorithm combines symbolic information with dynamic analysis and has two key advantages: It does not require any change in the underlying test data generation technique and it avoids many problems traditionally associated with symbolic execution, in particular the presence of loops. We have evaluated the algorithm on industrial closed source and open source systems using both local and global search-based testing techniques, demonstrating that both are statistically significantly more efficient using our approach. The test for significance was done using a one-sided, paired Wilcoxon signed rank test. On average, the local search requires 23.41% and the global search 7.78% fewer fitness evaluations when using a symbolic execution based fitness function generated by the algorithm.