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Analyzing developer contributions using artifact traceability graphs

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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.


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.


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.


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.


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.

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We would like to thank anonymous reviewers for their constructive comments, which helped to improve the paper.

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Correspondence to H. Alperen Çetin.

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Communicated by: Tim Menzies and Mei Nagappan

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Çetin, H.A., Tüzün, E. Analyzing developer contributions using artifact traceability graphs. Empir Software Eng 27, 77 (2022).

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