The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Generating software test data by evolution
Abstract
This paper discusses the use of genetic algorithms (GAs) for automatic software test data generation. This research extends previous work on dynamic test data generation where the problem of test data generation is reduced to one of minimizing a function. In our work, the function is minimized by using one of two genetic algorithms in place of the local minimization techniques used in earlier research. We describe the implementation of our GA-based system and examine the effectiveness of this approach on a number of programs, one of which is significantly larger than those for which results have previously been reported in the literature. We also examine the effect of program complexity on the test data generation problem by executing our system on a number of synthetic programs that have varying complexities.
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Citations
Cites
An Introduction to Genetic Algorithms
Mitchell, M. (1996) · doi:10.7551/mitpress/3927.001.0001 · Cited by 11,340
Cited by
Search‐based software test data generation: a survey
McMinn, P. (2004) · Software Testing, Verification and Reliability · doi:10.1002/stvr.294 · Cited by 1,368
GenProg: A Generic Method for Automatic Software Repair
Le Goues, C., Nguyen, T., Forrest, S., & Weimer, W. (2012) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2011.104 · Cited by 1,085
An orchestrated survey of methodologies for automated software test case generation
Anand, S., Burke, E. K., Chen, T. Y., Clark, J., Cohen, M. B., Grieskamp, W., Harman, M., Harrold, M. J., McMinn, P., Bertolino, A., et al. (2013) · Journal of Systems and Software · doi:10.1016/j.jss.2013.02.061 · Cited by 668
A Theoretical and Empirical Study of Search-Based Testing: Local, Global, and Hybrid Search
Harman, M., & McMinn, P. (2010) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2009.71 · Cited by 400
Is the cure worse than the disease? overfitting in automated program repair
Smith, E. K., Barr, E. T., Le Goues, C., & Brun, Y. (2015) · Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering · doi:10.1145/2786805.2786825 · Cited by 323
Metadata
- Authors
- Michael, C. C., McGraw, G., & Schatz, M. A.
- Venue
- IEEE Transactions on Software Engineering
- Published
- 2001
- Volume
- 27
- Issue
- 12
- Pages
- 1085-1110
- ISSN
- 0098-5589 (ISSN-L)
- OpenAlex
- W2128705399
- Cited by
- 478
- References
- 1
- FWCI
- 54.77
- Type
- journal article
- Language
- en
- Open access
- closed
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- Michael, C. C., McGraw, G., & Schatz, M. A. (2001). Generating software test data by evolution. IEEE Transactions on Software Engineering. https://doi.org/10.1109/32.988709
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
