The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
EvoSuite: automatic test suite generation for object-oriented software
Abstract
To find defects in software, one needs test cases that execute the software systematically, and oracles that assess the correctness of the observed behavior when running these test cases. This paper presents EvoSuite, a tool that automatically generates test cases with assertions for classes written in Java code. To achieve this, EvoSuite applies a novel hybrid approach that generates and optimizes whole test suites towards satisfying a coverage criterion. For the produced test suites, EvoSuite suggests possible oracles by adding small and effective sets of assertions that concisely summarize the current behavior; these assertions allow the developer to detect deviations from expected behavior, and to capture the current behavior in order to protect against future defects breaking this behavior.
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Citations
Cites
DART: directed automated random testing
Godefroid, P., Klarlund, N., & Sen, K. (2005) · ACM SIGPLAN Notices · doi:10.1145/1064978.1065036 · Cited by 2,067
DART: directed automated random testing
Godefroid, P., Klarlund, N., & Sen, K. (2005) · Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation · doi:10.1145/1065010.1065036 · Cited by 1,570
Pex–White Box Test Generation for .NET
Tillmann, N., & de Halleux, J. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-79124-9_10 · Cited by 791
Randoop: feedback-directed random testing for Java
Pacheco, C., & Ernst, M. D. (2007) · Companion to the 22nd ACM SIGPLAN conference on Object-oriented programming systems and applications companion · doi:10.1145/1297846.1297902 · Cited by 558
JCrasher: an automatic robustness tester for Java
Csallner, C., & Smaragdakis, Y. (2004) · Software: Practice and Experience · doi:10.1002/spe.602 · Cited by 426
Evolutionary testing of classes
Tonella, P. (2004) · Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis · doi:10.1145/1007512.1007528 · Cited by 410
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
Investigations of the software testing coupling effect
Offutt, A. J. (1992) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/125489.125473 · Cited by 371
Harman, M., Hu, L., Hierons, R., Wegener, J., Sthamer, H., Baresel, A., & Roper, M. (2004) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2004.1265732 · Cited by 265
Mutation-driven generation of unit tests and oracles
Fraser, G., & Zeller, A. (2010) · International Symposium on Software Testing and Analysis · doi:10.1145/1831708.1831728 · Cited by 159
Self-citation
Cited by
Defects4J: a database of existing faults to enable controlled testing studies for Java programs
Just, R., Jalali, D., & Ernst, M. D. (2014) · Proceedings of the 2014 International Symposium on Software Testing and Analysis · doi:10.1145/2610384.2628055 · Cited by 1,447
Fraser, G., & Arcuri, A. (2013) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2012.14 · Cited by 586
Self-citationCodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
Lu, S., Guo, D., Ren, S., Huang, J., Svyatkovskiy, A., Blanco, A., Clement, C., Drain, D., Jiang, D., Tang, D., et al. (2021) · arXiv · doi:10.48550/arxiv.2102.04664 · Cited by 536
FairFuzz: a targeted mutation strategy for increasing greybox fuzz testing coverage
Lemieux, C., & Sen, K. (2018) · Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering · doi:10.1145/3238147.3238176 · Cited by 477
An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation
Schäfer, M., Nadi, S., Eghbali, A., & Tip, F. (2024) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2023.3334955 · Cited by 431
“This fact has inspired extensive research on techniques for automated test generation including fuzzing [5], [6], feedback-directed random test generation [7], [8], [9], [10], [11], dynamic symbolic execution [12], [13], [14], [15], and search-based and evolutionary techniques [16], [17].”
Influential
Metadata
- Authors
- Fraser, G., & Arcuri, A.
- Venue
- Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
- Publisher
- ACM
- Published
- 2011-09-09
- Pages
- 416-419
- OpenAlex
- W1971650562
- Cited by
- 1,110
- References
- 15
- FWCI
- 23.00
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Fraser, G., & Arcuri, A. (2011). EvoSuite: automatic test suite generation for object-oriented software. Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering. https://doi.org/10.1145/2025113.2025179
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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.
