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

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 an...

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Detalles Bibliográficos
Autores principales: Rath, Michael, Mäder, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6557728/
https://www.ncbi.nlm.nih.gov/pubmed/31198827
http://dx.doi.org/10.1016/j.dib.2019.104005
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author Rath, Michael
Mäder, Patrick
author_facet Rath, Michael
Mäder, Patrick
author_sort Rath, Michael
collection PubMed
description 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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spelling pubmed-65577282019-06-13 The SEOSS 33 dataset — Requirements, bug reports, code history, and trace links for entire projects Rath, Michael Mäder, Patrick Data Brief Computer Science 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. Elsevier 2019-05-24 /pmc/articles/PMC6557728/ /pubmed/31198827 http://dx.doi.org/10.1016/j.dib.2019.104005 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Computer Science
Rath, Michael
Mäder, Patrick
The SEOSS 33 dataset — Requirements, bug reports, code history, and trace links for entire projects
title The SEOSS 33 dataset — Requirements, bug reports, code history, and trace links for entire projects
title_full The SEOSS 33 dataset — Requirements, bug reports, code history, and trace links for entire projects
title_fullStr The SEOSS 33 dataset — Requirements, bug reports, code history, and trace links for entire projects
title_full_unstemmed The SEOSS 33 dataset — Requirements, bug reports, code history, and trace links for entire projects
title_short The SEOSS 33 dataset — Requirements, bug reports, code history, and trace links for entire projects
title_sort seoss 33 dataset — requirements, bug reports, code history, and trace links for entire projects
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6557728/
https://www.ncbi.nlm.nih.gov/pubmed/31198827
http://dx.doi.org/10.1016/j.dib.2019.104005
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