How does developer interaction relate to software quality? an examination of product development data
Industrial software systems are being increasingly developed by large and distributed teams. Tools like collaborative development environments (CDE) are used to facilitate interaction between members of such teams, with the expectation that social factors around the interaction would facilitate team...
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2018
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| Online Access: | https://ink.library.smu.edu.sg/sis_research/5579 https://ink.library.smu.edu.sg/context/sis_research/article/6582/viewcontent/HowDoesDeveloperInteraction_2018_av.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Industrial software systems are being increasingly developed by large and distributed teams. Tools like collaborative development environments (CDE) are used to facilitate interaction between members of such teams, with the expectation that social factors around the interaction would facilitate team functioning. In this paper, we first identify typically social characteristics of interaction in a software development team: reachability, connection, association, and clustering. We then examine how these factors relate to the quality of software produced by a team, in terms of the number of defects, through an empirical study of 70+ teams, involving 900+ developers in total, spread across 30+ locations and 19 time-zones, working on 40,000+ units of work in the multi-version development of a major industrial product, spreading across more than five years. After controlling for known factors affecting large scale distributed development such as dependency, system age, developer expertise and experience, geographic dispersion, socio-technical congruence, and the number of files changed, we find statistically significant effects of connection and clustering on software quality. Higher levels of intra-team connection are found to relate to higher defect count, whereas more clustering relates to fewer defects. We examine the implications of these results for individual developers, project managers, and organizations. |
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