Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

9-2020

Abstract

Context: In a seminal work, Ball et al. [1] investigate if the information available in version control systems could be used to predict defect density, arguing that practitioners and researchers could better understand errors "if [our] version control system could talk". In the meanwhile, several research works have reported that conflict merge resolution is a time consuming and error-prone task, while other contributions diverge about the correlation between co-change dependencies and defect density. Problem: The correlation between conflicting merge scenarios and bugs has not been addressed before, whilst the correlation between co-change dependencies and bug density has been only investigated using a small number of case studies-which can compromise the generalization of the results. Goal: To address this gap in the literature, this paper presents the results of a comprehensive study whose goal is to understand whether or not (a) conflicting merge scenarios and (b) co-change dependencies are good predictors for bug density. Method: We first build a curated dataset comprising the source code history of 29 popular Java Apache projects and leverage the SZZ algorithm to collect the sets of bug-fixing and bug-introducing commits. We then combine the SZZ results with the set of past conflicting merge scenarios and co-change dependencies of the projects. Finally, we use exploratory data analysis and machine learning models to understand the strength of the correlation between conflict resolution and co-change dependencies with defect density. Findings: (a) conflicting merge scenarios are not more prone to introduce bugs than regular commits, (b) there is a negligible to a small correlation between co-change dependencies and defect density-contradicting previous studies in the literature.

Keywords

Software defects, software integration, merge conflicts, co-change dependencies

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

2020 36th IEEE International Conference on Software Maintenance and Evolution (ICSME): September 27- October 3, Adelaide, Virtual: Proceedings

First Page

441

Last Page

452

ISBN

9781728156194

Identifier

10.1109/ICSME46990.2020.00049

Publisher

IEEE Computer Society

City or Country

Los Alamitos, CA

Copyright Owner and License

Publisher

Additional URL

https://doi.org/10.1109/ICSME46990.2020.00049

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