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

Rath, Michael and Mäder, Patrick (2019) The SEOSS 33 dataset --- Requirements, bug reports, code history, and trace links for entire projects. Data in Brief, 25 (104005). Elsevier. doi: 10.1016/j.dib.2019.104005. ISSN 2352-3409.

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Official URL: https://doi.org/10.1016%2Fj.dib.2019.104005

Abstract

This paper provides a systematically retrieved dataset consisting of 33 open-source software projects containing a largenumber 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.

Item URL in elib:https://elib.dlr.de/128197/
Document Type:Article
Title:The SEOSS 33 dataset --- Requirements, bug reports, code history, and trace links for entire projects
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Rath, MichaelUNSPECIFIEDhttps://orcid.org/0000-0001-8938-3690UNSPECIFIED
Mäder, PatrickUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:2019
Journal or Publication Title:Data in Brief
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:25
DOI:10.1016/j.dib.2019.104005
Publisher:Elsevier
ISSN:2352-3409
Status:Published
Keywords:Mining software repositories, Data collection, Data mining, Requirements analysis, Traceability, Bug localization, Issue tracking, Changeset data
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:other
DLR - Research area:Raumfahrt
DLR - Program:R - no assignment
DLR - Research theme (Project):R - no assignment
Location: Jena
Institutes and Institutions:Institute of Data Science
Institute of Data Science > IT-Security
Institute of Data Science > Secure Digital Systems
Deposited By: Heinze, Thomas
Deposited On:19 Sep 2019 07:55
Last Modified:02 Jul 2020 14:57

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