HomoTR
| Autor: | Chunrong Fang, Weisong Sun, Chenqian Zhu, Qin Liu, Yong Huang, Yangyang Yuan |
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| Rok vydání: | 2020 |
| Předmět: |
Matching (statistics)
Unit testing Computer science business.industry Code coverage Process (computing) 020207 software engineering 02 engineering and technology Recommender system Test (assessment) Test case 0202 electrical engineering electronic engineering information engineering Code (cryptography) Software engineering business |
| Zdroj: | ASE |
| DOI: | 10.1145/3324884.3415296 |
| Popis: | A growing number of new technologies are used in test development. Among them, automatic test generation, a promising technology to improve the efficiency of unit testing, currently performs not satisfactory in practice. Test recommendation, like code recommendation, is another feasible technology for supporting efficient unit testing and gets increasing attention. In this paper, we develop a novel system, namely HomoTR, which implements online test recommendations by measuring the homology of two methods. If the new method under test shares homology with an existing method that has test cases, HomoTR will recommend the test cases to the new method. The preliminary experiments show that HomoTR can quickly and effectively recommend test cases to help the developers improve the testing efficiency. Besides, HomoTR has been integrated into the MoocTest platform successfully, so it can also execute the recommended test cases automatically and visualize the testing results (e.g., Branch Coverage) friendly to help developers understand the process of testing. The demo video of HomoTR can be found at https://youtu.be/_227EfcUbus. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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