Evolutionary testing for crash reproduction

Evolutionary testing for crash reproduction

Soltani, M. (TU Delft Software Engineering)
Panichella, A. (TU Delft Software Engineering)
van Deursen, A. (TU Delft Software Technology)

Software Technology

2016-05-14

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.

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

http://resolver.tudelft.nl/uuid:e0bda3c9-3757-4ff1-b9cf-bcd5835d5e77

https://doi.org/10.1145/2897010.2897015

Association for Computing Machinery (ACM), New York

9781450341660

Proceedings - 9th International Workshop on Search-Based Software Testing, SBST 2016

9th International Workshop on Search-Based Software Testing, SBST 2016, 2016-05-16 → 2016-05-17, Austin, United States

Institutional Repository

conference paper

© 2016 M. Soltani, A. Panichella, A. van Deursen