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

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 var...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Abdulkadir Şeker [verfasserIn] Banu Diri [verfasserIn] Halil Arslan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	developer metric open source project recommendation system GitHub issue pull request

Übergeordnetes Werk:	In: Applied Sciences - MDPI AG, 2012, 11(2021), 3, p 920
Übergeordnetes Werk:	volume:11 ; year:2021 ; number:3, p 920

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/app11030920

Katalog-ID:	DOAJ050845187

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title_sort	new developer metrics for open source software development challenges: an empirical study of project recommendation systems
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abstract	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-<i<n</i< hit scores using two different approaches. The results for all scores with these methods indicated that the most successful metrics were <i<binary_issue_related</i<, <i<issue_commented</i<, <i<binary_pr_related</i<, and <i<issue_opened</i<. 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.
abstractGer	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-<i<n</i< hit scores using two different approaches. The results for all scores with these methods indicated that the most successful metrics were <i<binary_issue_related</i<, <i<issue_commented</i<, <i<binary_pr_related</i<, and <i<issue_opened</i<. 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.
abstract_unstemmed	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-<i<n</i< hit scores using two different approaches. The results for all scores with these methods indicated that the most successful metrics were <i<binary_issue_related</i<, <i<issue_commented</i<, <i<binary_pr_related</i<, and <i<issue_opened</i<. 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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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. 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score	7.400572

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

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