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Register a new userDo Communities in Developer Interaction Networks align with Subsystem Developer Teams? An Empirical Study of Open Source Systems
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Added by
Usman Ashraf
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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Studies over the past decade demonstrated that developers contributing to open source software systems tend to self-organize in emerging communities. This latent community structure has a significant impact on software quality. While several approaches address the analysis of developer interaction networks, the question of whether these emerging communities align with the developer teams working on various subsystems remains unanswered. Work on socio-technical congruence implies that people that work on the same task or artifact need to coordinate and thus communicate, potentially forming stronger interaction ties. Our empirical study of 10 open source projects revealed that developer communities change considerably across a projects lifetime (hence implying that relevant relations between developers change) and that their alignment with subsystem developer teams is mostly low. However, subsystems teams tend to remain more stable. These insights are useful for practitioners and researchers to better understand developer interaction structure of open source systems.
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The open source development model has become a paradigm shift from traditional in-house/closed-source software development model, with many successes. Traditionally, open source projects were characterized essentially by their individual volunteer developers. Such tradition has changed significantly with the participation of many organizations in particular. However, there exists a knowledge gap concerning how open source developer communities evolve. In this paper, we present some observations on open source developer communities. In particular, we analyze git repositories of 20 well-known open source projects, with over 3 million commit activities in total. The analysis has been carried out in three respects, productivity, diversity and growth using the Spearmans rank correlation coefficient, diversity index and the Gompertz/logistic curves, respectively. We find out that (a) the Spearmans rank correlation coefficient between active contributors and commit activities reveals how changes in the size of the developer community impacts the productivity of the community; (b) the diversity index of an open source developer community reveals the structure of the community; and (c) the growth of open source developer communities can be described using different phases of growth curves as in many organic matters.
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Eclipse, an open source software project, acknowledges its donors by presenting donation badges in its issue tracking system Bugzilla. However, the rewarding effect of this strategy is currently unknown. We applied a framework of causal inference to investigate relative promptness of developer response to bug reports with donation badges compared with bug reports without the badges, and estimated that donation badges decreases developer response time by a median time of about two hours. The appearance of donation badges is appealing for both donors and organizers because of its practical, rewarding and yet inexpensive effect.
Automated program repair is an emerging technology that seeks to automatically rectify bugs and vulnerabilities using learning, search, and semantic analysis. Trust in automatically generated patches is necessary for achieving greater adoption of program repair. Towards this goal, we survey more than 100 software practitioners to understand the artifacts and setups needed to enhance trust in automatically generated patches. Based on the feedback from the survey on developer preferences, we quantitatively evaluate existing test-suite based program repair tools. We find that they cannot produce high-quality patches within a top-10 ranking and an acceptable time period of 1 hour. The developer feedback from our qualitative study and the observations from our quantitative examination of existing repair tools point to actionable insights to drive program repair research. Specifically, we note that producing repairs within an acceptable time-bound is very much dependent on leveraging an abstract search space representation of a rich enough search space. Moreover, while additional developer inputs are valuable for generating or ranking patches, developers do not seem to be interested in a significant human-in-the-loop interaction.
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