Publication Type
Journal Article
Version
publishedVersion
Publication Date
11-2022
Abstract
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.
Keywords
tangled changes, tangled commits, bug fix, manual validation, research turk, registered report
Discipline
Databases and Information Systems | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
Empirical Software Engineering
Volume
27
Issue
6
First Page
1
Last Page
49
ISSN
1382-3256
Identifier
10.1007/s10664-021-10083-5
Publisher
Springer
Citation
HERBOLD, Steffen; TRAUTSCH, Alexander; LEDEL, Benjamin; AGHAMOHAMMADI, Alireza; GHALEB, Taher Ahmed; KAUR CHAHAL, Kuljit; BOSSENMAIER, Tim; NAGARIA, Bhaveet; MAKEDONSKI, Philip; AHMADABADI, Matin Nili; SZABADOS, Kristóf; SPIEKER, Helge; MADEJA, Matej; HOY, Nathaniel G.; TREUDE, Christoph; WANG, Shangwen; RODRÍGUEZ-PÉREZ, Gema; COLOMO-PALACIOS, Ricardo; VERDECCHIA, Roberto; and SINGH, Paramvir.
A fine-grained data set and analysis of tangling in bug fixing commits. (2022). Empirical Software Engineering. 27, (6), 1-49.
Available at: https://ink.library.smu.edu.sg/sis_research/8762
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/s10664-021-10083-5