Analyzing developer contributions using artifact traceability graphs

Çetin, H. Alperen; Tüzün, Eray

doi:10.1007/s10664-022-10129-2

Cited by 3 publications

(7 citation statements)

References 49 publications

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“…Regarding the specific information for maintaining trace links, Luders et al noted that it is difficult to maintain an overview of dependencies among issues [32]. Çetin et al focused on identifying the contributions of developers based on traceability graphs [55].…”

Section: ) Informationmentioning

confidence: 99%

“…The fourth one sought to generate trace links between architectural issues and code changes [48]. The last source discussed identifying developer contributions by building traceability graphs of developers based on issues and commits [55].…”

Section: ) Issue Reports and Commitsmentioning

confidence: 99%

“…The study in [33] used the design science research method proposed by Wieringa [70] to propose a framework for designing traceability strategies. The study in [55] used the NetworkX package to analyze the social network of developers based on issues and commits.…”

Section: ) Other Approachesmentioning

confidence: 99%

“…Five studies used open datasets. The study in [55] used SEOSS 33 [71], datasets for 33 OSS projects. The study in [55] selected Apache Hadoop, Apache Hive, Apache Pig, Apache HBase, Apache Derby, and Apache Zookeeper projects from the datasets for an evaluation.…”

Section: ) Experiments With Open Datasetsmentioning

confidence: 99%

“…The study in [55] used SEOSS 33 [71], datasets for 33 OSS projects. The study in [55] selected Apache Hadoop, Apache Hive, Apache Pig, Apache HBase, Apache Derby, and Apache Zookeeper projects from the datasets for an evaluation. The study in [25] used two datasets: CodeSearchNet and a database that consisted of 3 open-source projects.…”

Section: ) Experiments With Open Datasetsmentioning

confidence: 99%

See 4 more Smart Citations

A Systematic Literature Review of Issue-Based Requirement Traceability

et al. 2023

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Issue reports are software artifacts that often specify the changed requirements of software systems. As software systems evolve according to these changed requirements, issue reports have become the essential artifacts that should be covered by requirement traceability. While researchers have developed automatic approaches for establishing the traceability links of issue reports, no papers have surveyed these approaches. In this paper, we conduct a systematic literature review of issue-based requirement traceability. We searched for articles published in renowned conferences and journals in the software engineering field from 2011 to 2022. From 1,347 initial articles, we identified 40 relevant articles. We investigated four aspects of issue-based traceability: problems, artifact pairs, techniques, and evaluation targets. Our findings are as follows. First, the challenges of issue-based requirement traceability are relevant to accuracy, effort, support, information, and trustworthiness. Second, issue reports are linked to commits, source code, user reviews, and test cases. Third, the studies mainly adopted machine learning and information retrieval techniques to generate and recover trace links. Finally, the main evaluation targets were open-source projects, but open datasets were also provided.

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Section: ) Informationmentioning

confidence: 99%

Section: ) Issue Reports and Commitsmentioning

confidence: 99%

Section: ) Other Approachesmentioning

confidence: 99%

Section: ) Experiments With Open Datasetsmentioning

confidence: 99%

Section: ) Experiments With Open Datasetsmentioning

confidence: 99%

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A Systematic Literature Review of Issue-Based Requirement Traceability

et al. 2023

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Balanced knowledge distribution among software development teams—Observations from open‐ and closed‐source software development

Shafiq,

Mayr‐Dorn,

Mashkoor

et al. 2024

J Software Evolu Process

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SummaryIn software development, developer turnover is among the primary reasons for project failures, leading to a great void of knowledge and strain for newcomers. Unfortunately, no established methods exist to measure how the problem domain knowledge is distributed among developers. Awareness of how this knowledge evolves and is owned by key developers in a project helps stakeholders reduce risks caused by turnover. To this end, this paper introduces a novel, realistic representation of problem domain knowledge distribution: the ConceptRealm. To construct the ConceptRealm, we employ a latent Dirichlet allocation model to represent textual features obtained from 300 K issues and 1.3 M comments from 518 open‐source projects. We analyze whether the newly emerged issues and developers share similar concepts or how aligned the individual developers' concepts are with the team over time. We also investigate the impact of leaving developers on the frequency of concepts. Finally, we also evaluate the soundness of our approach on a closed‐source software project, thus allowing the validation of the results from a practical standpoint. We find out that the ConceptRealm can represent the problem domain knowledge within a project and can be utilized to predict the alignment of developers with issues. We also observe that projects exhibit many keepers independent of project maturity and that abruptly leaving keepers correlates with a decline of their core concepts as the remaining developers cannot quickly familiarize themselves with those concepts.

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