Traceability recovery between bug reports and test cases-a Mozilla Firefox case study

Gadelha, Guilherme; Ramalho, Franklin; Massoni, Tiago

doi:10.1007/s10515-021-00287-w

Cited by 10 publications

(6 citation statements)

References 43 publications

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“…Four studies linked issue reports to test cases [31], [39], [45], [47]. One study focused on establishing trace links between requirements and test cases by using issue reports as requirements [39].…”

Section: ) Issue Reports and Test Casesmentioning

confidence: 99%

“…One study focused on establishing trace links between requirements and test cases by using issue reports as requirements [39]. Three studies recovered the trace links between issue reports and test cases [31], [45], [47]. The studies intended to link bugs and test cases.…”

Section: ) Issue Reports and Test Casesmentioning

confidence: 99%

“…In 2020 and 2021, two studies used a hybrid of IR and ML techniques [45] [31]. The study in [45] combined similarity metrics with LSI, LDA, BM25, and convolutional neural networks.…”

Section: ) Ir-based and Ml-based Approachesmentioning

confidence: 99%

“…The study in [45] combined similarity metrics with LSI, LDA, BM25, and convolutional neural networks. Additionally, the study in [31], a follow-up study to [45], also used the same techniques (i.e., LSI, LDA, BM25, etc.) and vectorized issue reports as input queries and test cases as target sources.…”

Section: ) Ir-based and Ml-based Approachesmentioning

confidence: 99%

“…Fifth, the study in [45] and its follow-up study [31] used Mozilla Firefox open-source projects to evaluate the accuracy of the trace links generated by their proposed approaches.…”

Section: ) Experiments With Open-source Projectsmentioning

confidence: 99%

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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: ) Issue Reports and Test Casesmentioning

confidence: 99%

Section: ) Issue Reports and Test Casesmentioning

confidence: 99%

“…In 2020 and 2021, two studies used a hybrid of IR and ML techniques [45] [31]. The study in [45] combined similarity metrics with LSI, LDA, BM25, and convolutional neural networks.…”

Section: ) Ir-based and Ml-based Approachesmentioning

confidence: 99%

Section: ) Ir-based and Ml-based Approachesmentioning

confidence: 99%

“…Fifth, the study in [45] and its follow-up study [31] used Mozilla Firefox open-source projects to evaluate the accuracy of the trace links generated by their proposed approaches.…”

Section: ) Experiments With Open-source Projectsmentioning

confidence: 99%

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