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Studying the impact of social interactions on software quality

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Abstract

Correcting software defects accounts for a significant amount of resources in a software project. To make best use of testing efforts, researchers have studied statistical models to predict in which parts of a software system future defects are likely to occur. By studying the mathematical relations between predictor variables used in these models, researchers can form an increased understanding of the important connections between development activities and software quality. Predictor variables used in past top-performing models are largely based on source code-oriented metrics, such as lines of code or number of changes. However, source code is the end product of numerous interlaced and collaborative activities carried out by developers. Traces of such activities can be found in the various repositories used to manage development efforts. In this paper, we develop statistical models to study the impact of social interactions in a software project on software quality. These models use predictor variables based on social information mined from the issue tracking and version control repositories of two large open-source software projects. The results of our case studies demonstrate the impact of metrics from four different dimensions of social interaction on post-release defects. Our findings show that statistical models based on social information have a similar degree of explanatory power as traditional models. Furthermore, our results demonstrate that social information does not substitute, but rather augments traditional source code-based metrics used in defect prediction models.

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Notes

  1. http://pmd.sourceforge.net/

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Acknowledgements

We want to thank Audris Mockus of Avaya Labs and the anonymous reviewers of ICPC ’10 for their many helpful comments on earlier revisions of this study.

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Authors and Affiliations

  1. Software Analysis and Intelligence Lab (SAIL), Queen’s University, School of Computing, 156, Barrie Street, Kingston, ON, K7L 3N6, Canada

    Nicolas Bettenburg & Ahmed E. Hassan

Authors
  1. Nicolas Bettenburg
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  2. Ahmed E. Hassan
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Corresponding author

Correspondence to Nicolas Bettenburg.

Additional information

Editor: Giulio Antoniol and Keith Gallagher

Appendices

Appendix A: Repeatability of our Work

We have carried out most of our statistical analyses in a statistical tool called R, which is a widely used open-source implementation of the commercial S programming language, originally developed by John Chambers at Bell Labs. For further information and downloads, we direct our interested reader to http://cran.r-project.org/. In order to provide a common ground for future research in this area, and to enable repeatability of our work, we present the source code for all our analyses carried out in this study in this Appendix. In addition to the R scripts, we provide the datasets for both case studies under the following URL: http://sailhome.cs.queensu.ca/replication/social-interactions/.

1.1 Case Study One: ECLIPSE

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Appendix B: Summary of Hierarchical Models with β-coefficients

Table 17 Hierarchical analysis of logistic regression models along the four dimensions of social interaction metrics for ECLIPSE 3.0
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Table 18 Hierarchical analysis of logistic regression models along the four dimensions of social interaction metrics for ECLIPSE 3.1
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Table 19 Hierarchical analysis of logistic regression models along the four dimensions of social interaction metrics for ECLIPSE 3.2
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Table 20 Hierarchical analysis of logistic regression models along the four dimensions of social interaction metrics for Mozilla FIREFOX 1.5
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Table 21 Hierarchical analysis of logistic regression models along the four dimensions of social interaction metrics for Mozilla FIREFOX 2.0
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Table 22 Hierarchical analysis of logistic regression models along the four dimensions of social interaction metrics for Mozilla FIREFOX 3.0
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Bettenburg, N., Hassan, A.E. Studying the impact of social interactions on software quality. Empir Software Eng 18, 375–431 (2013). https://doi.org/10.1007/s10664-012-9205-0

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