A fine-grained data set and analysis of tangling in bug fixing commits

• Published in: Empirical software engineering : an international journal Vol. 27; no. 6
• Main Authors: Herbold, Steffen, Trautsch, Alexander, Ledel, Benjamin, Aghamohammadi, Alireza, Ghaleb, Taher A., Chahal, Kuljit Kaur, Bossenmaier, Tim, Nagaria, Bhaveet, Makedonski, Philip, Ahmadabadi, Matin Nili, Szabados, Kristof, Spieker, Helge, Madeja, Matej, Hoy, Nathaniel, Lenarduzzi, Valentina, Wang, Shangwen, Rodríguez-Pérez, Gema, Colomo-Palacios, Ricardo, Verdecchia, Roberto, Singh, Paramvir, Qin, Yihao, Chakroborti, Debasish, Davis, Willard, Walunj, Vijay, Wu, Hongjun, Marcilio, Diego, Alam, Omar, Aldaeej, Abdullah, Amit, Idan, Turhan, Burak, Eismann, Simon, Wickert, Anna-Katharina, Malavolta, Ivano, Sulír, Matúš, Fard, Fatemeh, Henley, Austin Z., Kourtzanidis, Stratos, Tuzun, Eray, Treude, Christoph, Shamasbi, Simin Maleki, Pashchenko, Ivan, Wyrich, Marvin, Davis, James, Serebrenik, Alexander, Albrecht, Ella, Aktas, Ethem Utku, Strüber, Daniel, Erbel, Johannes
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-11-2022; Springer Nature B.V
• Subjects: Compilers; Computer Science; Datasets; Fixing; Interpreters; Programming Languages; Registered Reports; Software engineering; Software Engineering/Programming and Operating Systems; Source code; Tangling; Tangled commits; Bug fix; Manual validation; Registered report; Research turk; Tangled changes
• ISSN: 1382-3256; 1573-7616
• DOI: 10.1007/s10664-021-10083-5

Context
Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only bugs, but also other concerns irrelevant for the study of bugs.
Objective
We want to improve our understanding of the prevalence of tangling and the types of changes that are tangled within bug fixing commits.
Methods
We use a crowd sourcing approach for manual labeling to validate which changes contribute to bug fixes for each line in bug fixing commits. Each line is labeled by four participants. If at least three participants agree on the same label, we have consensus.
Results
We estimate that between 17% and 32% of all changes in bug fixing commits modify the source code to fix the underlying problem. However, when we only consider changes to the production code files this ratio increases to 66% to 87%. We find that about 11% of lines are hard to label leading to active disagreements between participants. Due to confirmed tangling and the uncertainty in our data, we estimate that 3% to 47% of data is noisy without manual untangling, depending on the use case.
Conclusion
Tangled commits have a high prevalence in bug fixes and can lead to a large amount of noise in the data. Prior research indicates that this noise may alter results. As researchers, we should be skeptics and assume that unvalidated data is likely very noisy, until proven otherwise.