Browsing by Subject "Artifact traceability graphs"

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Open Access
Analyzing developer contributions using artifact traceability graphs
(Springer New York LLC, 2022-03-28) Çetin, H. Alperen; Tüzün, Eray
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.
Open Access
Analyzing developer contributions using artifact traceability graphs
(2020-12) Çetin, Hamdi Alperen
Software artifacts are the by-products of the development process. Throughout the life cycle of a project, developers produce diﬀerent artifacts such as source ﬁles and bug reports. To analyze developer contributions, we construct artifact traceability graphs with these artifacts and their relations using the data from software development and collaboration tools. Developers are the main resource to build and maintain software projects. Since they keep the knowledge of the projects, developer turnover is a critical risk for software projects. From diﬀerent viewpoints, some developers can be valuable and indispensable for the project. They are the key developers of the project, and identifying them is a crucial task for managerial decisions. Regardless of whether they are key developers or not, when developers leave the project, their work should be transferred to other developers. Even though all developers continue to work on the project, the knowledge distribution can be imbalanced among developers. Evaluating knowledge distribution is important since it might be an early warning for future problems. We employ algorithms on artifact traceability graphs to identify key develop-ers, recommend replacements for leaving developers and evaluate knowledge distribution among developers. We conduct experiments on six open source projects: Hadoop, Hive, Pig, HBase, Derby and Zookeeper. Then, we 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 with the baseline approach up to 94%.
Open Access
Identifying key developers using artifact traceability graphs
(Association for Computing Machinery, 2020) Çetin, H. Alperen; Tüzün, Eray; Minku, L.; Menzies, T.; Nagappan, M.
Developers are the most important resource to build and maintain software projects. Due to various reasons, some developers take more responsibility, and this type of developers are more valuable and indispensable for the project. Without them, the success of the project would be at risk. We use the term key developers for these essential and valuable developers, and identifying them is a crucial task for managerial decisions such as risk assessment for potential developer resignations. We study key developers under three categories: jacks, mavens and connectors. A typical jack (of all trades) has a broad knowledge of the project, they are familiar with different parts of the source code, whereas mavens represent the developers who are the sole experts in specific parts of the projects. Connectors are the developers who involve different groups of developers or teams. They are like bridges between teams. To identify key developers in a software project, we propose to use traceable links among software artifacts such as the links between change sets and files. First, we build an artifact traceability graph, then we define various metrics to find key developers. We conduct experiments on three open source projects: Hadoop, Hive and Pig. To validate our approach, we use developer comments in issue tracking systems and demonstrate that the identified key developers by our approach match the top commenters up to 92%.