A Fine-grained Data Set and Analysis of Tangling in Bug Fixing Commits

Steffen Herbold (Corresponding author), Alexander Trautsch, Benjamin Ledel, Alireza Aghamohammadi, Taher Ahmed Ghaleb, Kuljit Kaur Chahal, Tim Bossenmaier, Bhaveet Nagaria, Philip Makedonski, Matin Nili Ahmadabadi, Kristóf Szabados, Helge Spieker, Matej Madeja, Nathaniel Hoy, Valentina Lenarduzzi, Shangwen Wang, Gema Rodriguez Perez, Ricardo Colomo-Palacios, Roberto Verdecchia, Paramvir SinghYihao Qin, Debasish Chakroborti, Willard Davis, Vijay Walunj, Hongjun Wu, Diego Marcilio, Omar Alam, Abdullah Aldaeej, Idan Amit, Burak Turhan, Simon Eismann, Anna-Katharina Wickert, Ivano Malavolta, Matúš Sulír, Fatemeh Fard, Austin Z Henley, Stratos Kourtzanidis, Eray Tüzün, Christoph Treude, Simin Maleki Shamasbi, Ivan Pashchenko, Marvin Wyrich, James C. Davis, Alexander Serebrenik, Ella Albrecht, Ethem Utku Aktas, Daniel Strüber, Johannes Erbel

Research output: Contribution to journalArticleAcademicpeer-review

11 Citations (Scopus)
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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.
Original languageEnglish
Article number125
Number of pages49
JournalEmpirical Software Engineering
Issue number6
Publication statusPublished - Nov 2022


  • Bug fix
  • Manual validation
  • Registered report
  • Research turk
  • Tangled changes
  • Tangled commits


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