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Context: Tangled commits are changes to software that address multipleconcerns at once. For researchers interested in bugs, tangled commits mean thatthey actually study not only bugs, but also other concerns irrelevant for thestudy of bugs.  Objective: We want to improve our understanding of the prevalence of tanglingand the types of changes that are tangled within bug fixing commits.  Methods: We use a crowd sourcing approach for manual labeling to validatewhich changes contribute to bug fixes for each line in bug fixing commits. Eachline is labeled by four participants. If at least three participants agree onthe same label, we have consensus.  Results: We estimate that between 17% and 32% of all changes in bug fixingcommits modify the source code to fix the underlying problem. However, when weonly 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 activedisagreements between participants. Due to confirmed tangling and theuncertainty in our data, we estimate that 3% to 47% of data is noisy withoutmanual untangling, depending on the use case.  Conclusion: Tangled commits have a high prevalence in bug fixes and can leadto a large amount of noise in the data. Prior research indicates that thisnoise may alter results. As researchers, we should be skeptics and assume thatunvalidated data is likely very noisy, until proven otherwise.

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