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Manual crash reproduction is a labor-intensive and time-consuming task. Therefore, several solutions have been proposed in literature for automatic crash reproduction, including generating unit tests via symbolic execution and mutation analysis. However, various limitations adversely affect the capabilities of the existing solutions in covering a wider range of crashes because generating helpful tests that trigger specific execution paths is particularly challenging. In this paper, we propose a new solution for automatic crash reproduction based on evolutionary unit test generation techniques. The proposed solution exploits crash data from collected stack traces to guide search-based algorithms toward the generation of unit test cases that can reproduce the original crashes. Results from our preliminary study on real crashes from Apache Commons libraries show that our solution can successfully reproduce crashes which are not reproducible by two other state-of-art techniques.

Original languageEnglish
Title of host publicationProceedings - 9th International Workshop on Search-Based Software Testing, SBST 2016
PublisherAssociation for computing machinery, Inc. (ACM)
Pages1-4
Number of pages4
ISBN (Electronic)9781450341660
DOIs
StatePublished - 14 May 2016
Event9th International Workshop on Search-Based Software Testing, SBST 2016 - Austin, United States

Conference

Conference9th International Workshop on Search-Based Software Testing, SBST 2016
CountryUnited States
CityAustin
Period16/05/1617/05/16

    Research areas

  • Crash reproduction, Genetic Algorithm, Search-based software testing, Test case generation

ID: 7664939