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Software testing is one of the very important Quality Assurance (QA)components. A lot of researchers deal with the testing process in terms oftester motivation and how tests should or should not be written. However, it isnot known from the recommendations how the tests are written in real projects.In this paper, the following was investigated: (i) the denotation of the word"test" in different natural languages; (ii) whether the number of occurrencesof the word "test" correlates with the number of test cases; and (iii) whattesting frameworks are mostly used. The analysis was performed on 38 GitHubopen source repositories thoroughly selected from the set of 4.3M GitHubprojects. We analyzed 20,340 test cases in 803 classes manually and 170kclasses using an automated approach. The results show that: (i) there exists aweak correlation (r = 0.655) between the number of occurrences of the word"test" and the number of test cases in a class; (ii) the proposed algorithmusing static file analysis correctly detected 97% of test cases; (iii) 15% ofthe analyzed classes used main() function whose represent regular Java programsthat test the production code without using any third-party framework. Theidentification of such tests is very complex due to implementation diversity.The results may be leveraged to more quickly identify and locate test cases ina repository, to understand practices in customized testing solutions, and tomine tests to improve program comprehension in the future.

Automating Test Case Identification in Java Open Source Projects on GitHub