On the Distribution of "Simple Stupid Bugs" in Unit Test Files: An Exploratory Study

This is the dataset that accompanies the study: "On the Distribution of "Simple Stupid Bugs" in Unit Test Files: An Exploratory Study." This study has been accepted for publication at the 2021 Mining Software Repositories Conference. Following is the abstract of the study: A key aspect of ensuring the quality of a software system is the practice of unit testing. Through unit tests, developers verify the correctness of production source code, thereby verifying the system's intended behavior under test. However, unit test code is subject to issues, ranging from bugs in the code to poor test case design (i.e., test smells). In this study, we compare and contrast the occurrences of a type of single-statement-bug-fix known as "simple stupid bugs" (SStuBs) in test and non-test (i.e., production) files in popular open-source Java Maven projects. Our results show that SStuBs occur more frequently in non-test files than in test files, with most fix-related code associated with assertion statements in test files. Further, most test files exhibiting SStuBs also exhibit test smells. We envision our findings enabling tool vendors to better support developers in improving the maintenance of test suites. Following are the contents of the dataset: Dataset.sqlite -- A SQLite database containing the raw dataset used in this project CompleteTableEntries.xlsx -- Excel spreadsheet containing the complete listings for the tables in the paper --------------------------------------------------------------------------------------------------------------------------- Key contents of Dataset.sqlite Table Name ---- Table Description "sstubs"---- The set of sstubs in popular Maven repositories "testsmells" ---- Mined test smells from test files "topJavaMavenProjects" ---- Repository details for the Maven projects "topJavaMaven_Commit" ---- Commit details for the Maven projects "topJavaMaven_CommitFile" ---- Files that were part of each commit ---------------------------------------------------------------------------------------------------------------------------This study is part of the work conducted by the Source Code Analysis And Natural Language Laboratory. For more information about what we do and to download the preprint of this study, visit: https://scanl.org