Surgical teams on GitHub: Modeling performance of GitHub project development processes

Jarczyk, Oskar; Jaroszewicz, Szymon; Wierzbicki, Adam; Pawlak, Kamil; Jankowski-Lorek, Michał

doi:10.1016/j.infsof.2018.03.010

Cited by 34 publications

(28 citation statements)

References 26 publications

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“…In the three-way interaction with coordinative complexity, the negative effect of knowledge loss was reversed as complexity increased. This suggests that although some abandoned code persisted in the project, the code was continually modified by a steady stream of newcomers and, in line with recent research on OSS teams (Jarczyk, Jaroszewicz, Wierzbicki, Pawlak, & Jankowski-Lorek, 2018), a small group of developers managed the task interdependencies introduced by newcomers in the project. We observed a similar effect with respect to the three-way interaction including component complexity.…”

Section: Resultsmentioning

confidence: 58%

Expertise and Complexity as Mediators of Knowledge Loss in Open Source Software Development

Newton

Fiore

Song

2019

Proceedings of the Human Factors and Ergonomics Society Annual

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This paper describes an approach integrating cognitive engineering with computational social science in the context of open source software (OSS) development. Through an analysis of large-scale collaborations in a complex operational setting, we study how expertise and task complexity predict changes in productivity when knowledge loss occurs. Using team data from thousands of software files, we model the effects of expertise, complexity, and knowledge loss on productivity. On its own, knowledge loss had a negative effect on productivity, but this effect was reversed when knowledge loss was combined with high complexity and high numbers of newcomers, suggesting that experts are better able to utilize crowdsourced work. We identify opportunities for research to inform prediction of outcomes in OSS projects based on team and task characteristics and demonstrate the value of integrating cognitive engineering with computational social science to study collaborative work in sociotechnical systems.

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Section: Resultsmentioning

confidence: 58%

Expertise and Complexity as Mediators of Knowledge Loss in Open Source Software Development

Newton

Fiore

Song

2019

Proceedings of the Human Factors and Ergonomics Society Annual

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“…[5] 1700 22,000 0.07 [26] 1255 58,092 0.02 [27] 1070 1600 0.66 [25] 62,607 9447 0.15 [30] 62,607 9447 0.15 Our study 100 41,280 0.002…”

Section: Paper Id Number Of User Number Of Project Ratio (~)mentioning

confidence: 76%

New Developer Metrics for Open Source Software Development Challenges: An Empirical Study of Project Recommendation Systems

2021

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Software collaboration platforms where millions of developers from diverse locations can contribute to the common open source projects have recently become popular. On these platforms, various information is obtained from developer activities that can then be used as developer metrics to solve a variety of challenges. In this study, we proposed new developer metrics extracted from the issue, commit, and pull request activities of developers on GitHub. We created developer metrics from the individual activities and combined certain activities according to some common traits. To evaluate these metrics, we created an item-based project recommendation system. In order to validate this system, we calculated the similarity score using two methods and assessed top-n hit scores using two different approaches. The results for all scores with these methods indicated that the most successful metrics were binary_issue_related, issue_commented, binary_pr_related, and issue_opened. To verify our results, we compared our metrics with another metric generated from a very similar study and found that most of our metrics gave better scores that metric. In conclusion, the issue feature is more crucial for GitHub compared with other features. Moreover, commenting activity in projects can be equally as valuable as code contributions. The most of binary metrics that were generated, regardless of the number of activities, also showed remarkable results. In this context, we presented improvable and noteworthy developer metrics that can be used for a wide range of open-source software development challenges, such as user characterization, project recommendation, and code review assignment.

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“…Some of the studies in this category focus on taking as the main information the commitments to follow up on issues that may occur in the project or with the developers, and that represent a challenge when executing software maintenance. Thus, the study 115 (Jarczyk et al, 2017), the closing of issues (errors and characteristics) is studied using it as main information for the analysis (commits) in software projects, which allows a better understanding of the factors that affect the completion rates of issues in software projects.…”

Section: Rq1 What Kind Of Information Is Taken As Input For the Analy...mentioning

confidence: 99%

A Systematic Mapping Study on Analysis of Code Repositories

Sayago-Heredia¹,

Pérez‐Castillo²,

Piattini³

2021

Informatica

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Code repositories contain valuable information, which can be extracted, processed and synthesized into valuable information. It enabled developers to improve maintenance, increase code quality and understand software evolution, among other insights. Certain research has been made during the last years in this field. This paper presents a systematic mapping study to find, evaluate and investigate the mechanisms, methods and techniques used for the analysis of information from code repositories that allow the understanding of the evolution of software. Through this mapping study, we have identified the main information used as input for the analysis of code repositories (commit data and source code), as well as the most common methods and techniques of analysis (empirical/experimental and automatic). We believe the conducted research is useful for developers working on software development projects and seeking to improve maintenance and understand the evolution of software through the use and analysis of code repositories.

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Surgical teams on GitHub: Modeling performance of GitHub project development processes

Cited by 34 publications

References 26 publications

Expertise and Complexity as Mediators of Knowledge Loss in Open Source Software Development

Expertise and Complexity as Mediators of Knowledge Loss in Open Source Software Development

New Developer Metrics for Open Source Software Development Challenges: An Empirical Study of Project Recommendation Systems

A Systematic Mapping Study on Analysis of Code Repositories

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