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      • Department of Computer Engineering
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      Analyzing developer contributions using artifact traceability graphs

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      Author(s)
      Çetin, H. Alperen
      Tüzün, Eray
      Date
      2022-03-28
      Source Title
      Empirical Software Engineering
      Print ISSN
      1382-3256
      Electronic ISSN
      1573-7616
      Publisher
      Springer New York LLC
      Volume
      27
      Issue
      3
      Pages
      1 - 49
      Language
      English
      Type
      Article
      Item Usage Stats
      12
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      2
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      Abstract
      Context In a software project, properly analyzing the contributions of developers could provide valuable insights for decision-makers. The contributions of a developer could be in many different forms such as committing and reviewing code, opening and resolving issues. Previous approaches mainly consider the commit-based contributions which provide an incomplete picture of developer contributions. Objective Different from the traditional commit-based approaches for analyzing developer contributions, we aim to provide a more holistic approach to reflect the rich set of software development activities using artifact traceability graphs. Method For analyzing the developer contributions, we propose a novel categorization of developers (Jacks, Mavens and Connectors) in a software project. We introduce a set of algorithms on artifact traceability graphs to identify key developers, recommend replacements for leaving developers and evaluate knowledge distribution among developers. Results We evaluate our proposed algorithms on six open-source projects and demonstrate that the identified key developers match the top commenters up to 98%, recommended replacements are correct up to 91% and identified knowledge distribution labels are compatible 94% on average with the baseline approaches. Conclusions The proposed algorithms using artifact traceability graphs for analyzing developer contributions could be used by software project decision-makers in several scenarios. (1) Identifying different types of key developers. (2) Finding a replacement developer in large teams. (3) Evaluating the overall knowledge distribution amongst developers to take early precautions.
      Keywords
      Key developers
      Social networks
      Artifact traceability graphs
      Developer replacement
      Developer turnover
      Knowledge distribution
      Permalink
      http://hdl.handle.net/11693/111297
      Published Version (Please cite this version)
      https://www.doi.org/10.1007/s10664-022-10129-2
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      • Department of Computer Engineering 1561
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