  Software testing is one of the very important Quality Assurance (QA)
components. A lot of researchers deal with the testing process in terms of
tester motivation and how tests should or should not be written. However, it is
not 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 occurrences
of the word "test" correlates with the number of test cases; and (iii) what
testing frameworks are mostly used. The analysis was performed on 38 GitHub
open source repositories thoroughly selected from the set of 4.3M GitHub
projects. We analyzed 20,340 test cases in 803 classes manually and 170k
classes using an automated approach. The results show that: (i) there exists a
weak 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 algorithm
using static file analysis correctly detected 97% of test cases; (iii) 15% of
the analyzed classes used main() function whose represent regular Java programs
that test the production code without using any third-party framework. The
identification of such tests is very complex due to implementation diversity.
The results may be leveraged to more quickly identify and locate test cases in
a repository, to understand practices in customized testing solutions, and to
mine tests to improve program comprehension in the future.
