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DOI: 10.14569/IJACSA.2022.0131292
PDF

Clustering-based Automated Requirement Trace Retrieval

Author 1: Nejood Hashim Al-walidi
Author 2: Shahira Shaaban Azab
Author 3: Abdelaziz Khamis
Author 4: Nagy Ramadan Darwish

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 12, 2022.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: The benefits of requirement traceability are well known and documented. The traceability links between requirements and code are fundamental in supporting different activities in the software development process, including change management and software maintenance. These links can be obtained using manual or automatic means. Manual trace retrieval is a time-consuming task. Automatic trace retrieval can be performed via various tools such as Information retrieval or machine learning techniques. Meanwhile, a big concern associated with automated trace retrieval is the low precision problem primarily caused by the term mismatches across documents to be traced. This study proposes an approach that addresses the term mismatch problem to obtain the greatest improvements in the trace retrieval accuracy. The proposed approach uses clustering in the automated trace retrieval process and performs an experimental evaluation against previous benchmarks. The results show that the proposed approach improves the trace retrieval precision.

Keywords: Requirements traceability; information retrieval; term mismatch problem; trace retrieval; TraceLab; clustering

Nejood Hashim Al-walidi, Shahira Shaaban Azab, Abdelaziz Khamis and Nagy Ramadan Darwish, “Clustering-based Automated Requirement Trace Retrieval” International Journal of Advanced Computer Science and Applications(IJACSA), 13(12), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131292

@article{Al-walidi2022,
title = {Clustering-based Automated Requirement Trace Retrieval},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131292},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131292},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {12},
author = {Nejood Hashim Al-walidi and Shahira Shaaban Azab and Abdelaziz Khamis and Nagy Ramadan Darwish}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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