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| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | On the Effectiveness of Manual and Automatic Unit Test Generation: Ten Years Later |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Page Range | 121 - 125 |
| Event Title | Proceedings of the 16th International Conference on Mining Software Repositories |
| Event Type | conference |
| Event Location | Montreal, Quebec, Canada |
| Event Start Date | January 1 - 2019 |
| Event End Date | January 1 - 2019 |
| Series Name | MSR '19 |
| Place of Publication | Piscataway, NJ, USA |
| Publisher | IEEE Press |
| Abstract Text | Good unit tests play a paramount role when it comes to foster and evaluate software quality. However, writing effective tests is an extremely costly and time consuming practice. To reduce such a burden for developers, researchers devised ingenious techniques to automatically generate test suite for existing code bases. Nevertheless, how automatically generated test cases fare against manually written ones is an open research question. In 2008, Bacchelli et al. conducted an initial case study comparing automatic and manually generated test suites. Since in the last ten years we have witnessed a huge amount of work on novel approaches and tools for automatic test generation, in this paper we revise their study using current tools as well as complementing their research method by evaluating these tools' ability in finding regressions. Preprint [https://doi.org/10.5281/zenodo. 2595232], dataset [https://doi.org/10.6084/m9.figshare.7628642]. |
| Official URL | https://doi.org/10.1109/MSR.2019.00028 |
| Digital Object Identifier | 10.1109/MSR.2019.00028 |
| Other Identification Number | merlin-id:17894 |
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