The IlmSeven Dataset

Rath, Michael; Rempel, Patrick; Mäder, Patrick

doi:10.1109/re.2017.18

Cited by 16 publications

(10 citation statements)

References 19 publications

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“…This affects the resulting association of recorded interaction logs to requirement issues and thus, the created trace links. However, the percentage of commits with issue IDs is similar to those reported for open source projects in Rath et al (2017). Companies' guidelines for using issue IDs in commit messages are even more stringent than in open source projects, e.g.…”

Section: Threats To Validitysupporting

confidence: 66%

“…The Git repository comprised 406 commits. 226 commits (55.67% of all commits) did contain a Jira issue ID which is a similar proportion as reported by others (Rath et al 2017). We excluded files as described in Section 4.1 from the Git repository.…”

Section: Source Code In the Git Version Control Systemmentioning

confidence: 62%

“…Commit-based linkage of requirement and source code is particularly relevant for I L Com . Rath et al (2017) have studied commit linkage. They report on a data set Ilm7 they created from seven open source projects for the purpose of evaluating traceability research.…”

Section: Related Workmentioning

confidence: 99%

“…It is a common developers' convention to use issue identifiers (IDs) in commit messages to link commits to requirements and bug reports (Bird et al 2009;Merten et al 2016a;Rath et al 2017Rath et al , 2018. Trace links then can be created automatically by linking all files affected by a commit with the requirement specified by the issue ID in the commit message.…”

Section: Introductionmentioning

confidence: 99%

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Interaction-based creation and maintenance of continuously usable trace links between requirements and source code

Hübner

Paech

2020

Empir Software Eng

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Trace links between requirements and code are beneficial for many software engineering tasks such as maintenance, program comprehension, and re-engineering. If trace links are created and used continuously during a project, they need to have high precision and recall to be useful. However, manual trace link creation is cumbersome and existing automatic trace link creation methods are typically only applied retrospectively and to structured requirements. Therefore, they focus on recall and accept manual effort to cope with low precision. Such manual effort is not acceptable continuously. Furthermore, the maintenance of existing links along with changing artefacts in a project is neglected in most automatic trace link creation approaches. Therefore, we developed and evaluated an interaction log-based trace link creation approach IL to continuously provide correct trace links during a project. IL links unstructured requirements specified in an issue tracker and source code managed in a version control system. In the latest version, I L Com , our approach uses the interactions of developers with files in an integrated development environment and issue identifiers provided in commit messages to create trace links continuously after each commit. In this paper, we present I L Com , its most recent evaluation study, and a systematic literature review (SLR) about trace link maintenance (TM). We also present a TM process for I L Com based on two approaches from our SLR. In the evaluation study, we show that precision of I L Com created links is above 90% and recall almost at 80%. In the SLR, we discuss 16 approaches. Our approach is the first trace link creation approach with very good precision and recall and integrated trace maintenance.

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Section: Threats To Validitysupporting

confidence: 66%

Section: Source Code In the Git Version Control Systemmentioning

confidence: 62%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Interaction-based creation and maintenance of continuously usable trace links between requirements and source code

Hübner

Paech

2020

Empir Software Eng

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“…4 ). It improves the technique used to create the “IlmSeven dataset” [13] , which aimed mainly to be a traceability dataset.…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

The SEOSS 33 dataset — Requirements, bug reports, code history, and trace links for entire projects

Rath

Mäder

2019

Data in Brief

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This paper provides a systematically retrieved dataset consisting of 33 open-source software projects containing a large number of typed artifacts and trace links between them. The artifacts stem from the projects' issue tracking system and source version control system to enable their joint analysis. Enriched with additional metadata, such as time stamps, release versions, component information, and developer comments, the dataset is highly suitable for empirical research, e.g., in requirements and software traceability analysis, software evolution, bug and feature localization, and stakeholder collaboration. It can stimulate new research directions, facilitate the replication of existing studies, and act as benchmark for the comparison of competing approaches. The data is hosted on Harvard Dataverse using DOI 10.7910/DVN/PDDZ4Q accessible via https://bit.ly/2wukCHc .

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