Targeted test input generation using symbolic-concrete backward execution

Peter Dinges, Gul A Agha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Knowing inputs that cover a specific branch or statement in a program is useful for debugging and regression testing. Symbolic backward execution (SBE) is a natural approach to find such targeted inputs. However, SBE struggles with complicated arithmetic, external method calls, and datadependent loops that occur in many real-world programs. We propose symcretic execution, a novel combination of SBE and concrete forward execution that can efficiently find targeted inputs despite these challenges. An evaluation of our approach on a range of test cases shows that symcretic execution finds inputs in more cases than concolic testing tools while exploring fewer path segments. Integration of our approach will allow test generation tools to fill coverage gaps and static bug detectors to verify candidate bugs with concrete test cases.

Original languageEnglish (US)
Title of host publicationASE 2014 - Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering
PublisherAssociation for Computing Machinery, Inc
Pages31-36
Number of pages6
ISBN (Electronic)9781450330138
DOIs
StatePublished - Jan 1 2014
Event29th ACM/IEEE International Conference on Automated Software Engineering, ASE 2014 - Vasteras, Sweden
Duration: Sep 15 2014Sep 19 2014

Publication series

NameASE 2014 - Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering

Other

Other29th ACM/IEEE International Conference on Automated Software Engineering, ASE 2014
CountrySweden
CityVasteras
Period9/15/149/19/14

Keywords

  • Backward execution
  • Concolic
  • Goal-directed
  • Symcretic

ASJC Scopus subject areas

  • Software

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  • Cite this

    Dinges, P., & Agha, G. A. (2014). Targeted test input generation using symbolic-concrete backward execution. In ASE 2014 - Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering (pp. 31-36). (ASE 2014 - Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering). Association for Computing Machinery, Inc. https://doi.org/10.1145/2642937.2642951