A multi-agent K-means with case-based reasoning for an automated quality assessment of software requirement specification
Automating the quality assessment of Software Requirement Specification poses major challenges related to the need for advanced algorithms to extract the SRS quality features, interpret the context of the features, formulate accurate assessment metrics, and document the shortcomings as well as possi...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023
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| Online Access: | http://eprints.uthm.edu.my/8723/ http://eprints.uthm.edu.my/8723/1/J15623_6f07f3ec314a1568f718a3e2a235512e.pdf |
| _version_ | 1848889479919566848 |
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| author | Jubair, Mohammed Ahmed Mostafa, Salama A. Mustapha, Aida Salamat, Mohamad Aizi Hamid Hassan, Mustafa Mohammed, Mazin Abed AL-Dhief, Fahad Taha |
| author_facet | Jubair, Mohammed Ahmed Mostafa, Salama A. Mustapha, Aida Salamat, Mohamad Aizi Hamid Hassan, Mustafa Mohammed, Mazin Abed AL-Dhief, Fahad Taha |
| author_sort | Jubair, Mohammed Ahmed |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | Automating the quality assessment of Software Requirement Specification poses major challenges related to the need for advanced algorithms to extract the SRS quality features, interpret the context of the features, formulate accurate assessment metrics, and document the shortcomings as well as possible improvements. In the existing methods, such as Reconstructed Automated Requirement Measurement, and Rendex, some major processes are still handled offline by humans (semi-automated) or encompass automating the measurement of a few quality attributes due to the mentioned challenges. This paper addressed this gap and proposed an Automated Quality Assessment of SRS (AQA-SRS) framework to assess the SRS documents by automatically extracting features related to 11 quality attributes through a deep analysis of the SRS textual content. Also, it constructs a flexible platform that is able to minimize the human expert’s role in the SRS assessment. The AQA-SRS framework integrates Natural Language Processing, K-means, Multi-agent, and Case-Based Reasoning. The AQA-SRS framework is evaluated by processing two standard SRS datasets and comparing the results with state-of-the-art methods and analysis by software engineering experts. The results show that the AQA-SRS framework effectively assesses the tested SRS documents and achieves a 78% total agreement with the tested methods and software engineering experts. |
| first_indexed | 2025-11-15T20:26:50Z |
| format | Article |
| id | uthm-8723 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:26:50Z |
| publishDate | 2023 |
| publisher | Wiley |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-87232023-05-16T02:32:01Z http://eprints.uthm.edu.my/8723/ A multi-agent K-means with case-based reasoning for an automated quality assessment of software requirement specification Jubair, Mohammed Ahmed Mostafa, Salama A. Mustapha, Aida Salamat, Mohamad Aizi Hamid Hassan, Mustafa Mohammed, Mazin Abed AL-Dhief, Fahad Taha QA75 Electronic computers. Computer science Automating the quality assessment of Software Requirement Specification poses major challenges related to the need for advanced algorithms to extract the SRS quality features, interpret the context of the features, formulate accurate assessment metrics, and document the shortcomings as well as possible improvements. In the existing methods, such as Reconstructed Automated Requirement Measurement, and Rendex, some major processes are still handled offline by humans (semi-automated) or encompass automating the measurement of a few quality attributes due to the mentioned challenges. This paper addressed this gap and proposed an Automated Quality Assessment of SRS (AQA-SRS) framework to assess the SRS documents by automatically extracting features related to 11 quality attributes through a deep analysis of the SRS textual content. Also, it constructs a flexible platform that is able to minimize the human expert’s role in the SRS assessment. The AQA-SRS framework integrates Natural Language Processing, K-means, Multi-agent, and Case-Based Reasoning. The AQA-SRS framework is evaluated by processing two standard SRS datasets and comparing the results with state-of-the-art methods and analysis by software engineering experts. The results show that the AQA-SRS framework effectively assesses the tested SRS documents and achieves a 78% total agreement with the tested methods and software engineering experts. Wiley 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/8723/1/J15623_6f07f3ec314a1568f718a3e2a235512e.pdf Jubair, Mohammed Ahmed and Mostafa, Salama A. and Mustapha, Aida and Salamat, Mohamad Aizi and Hamid Hassan, Mustafa and Mohammed, Mazin Abed and AL-Dhief, Fahad Taha (2023) A multi-agent K-means with case-based reasoning for an automated quality assessment of software requirement specification. IET Communications. pp. 1-17. https://doi.org/10.1049/cmu2.12555 |
| spellingShingle | QA75 Electronic computers. Computer science Jubair, Mohammed Ahmed Mostafa, Salama A. Mustapha, Aida Salamat, Mohamad Aizi Hamid Hassan, Mustafa Mohammed, Mazin Abed AL-Dhief, Fahad Taha A multi-agent K-means with case-based reasoning for an automated quality assessment of software requirement specification |
| title | A multi-agent K-means with case-based reasoning for an automated quality assessment of software requirement specification |
| title_full | A multi-agent K-means with case-based reasoning for an automated quality assessment of software requirement specification |
| title_fullStr | A multi-agent K-means with case-based reasoning for an automated quality assessment of software requirement specification |
| title_full_unstemmed | A multi-agent K-means with case-based reasoning for an automated quality assessment of software requirement specification |
| title_short | A multi-agent K-means with case-based reasoning for an automated quality assessment of software requirement specification |
| title_sort | multi-agent k-means with case-based reasoning for an automated quality assessment of software requirement specification |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.uthm.edu.my/8723/ http://eprints.uthm.edu.my/8723/ http://eprints.uthm.edu.my/8723/1/J15623_6f07f3ec314a1568f718a3e2a235512e.pdf |