Automated Features Extraction from Software Requirements Specification (SRS) Documents as The Basis of Software Product Line (SPL) Engineering
Extractive Software Product Line Engineering (SPLE) puts features on the foremost aspect in domain analysis that needs to be extracted from the existing system's artifact. Feature in SPLE, which is closely related to system functionality, has been previously studied to be extracted from source...
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| Format: | Article |
| Language: | English |
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University of Brawijaya
2020-12-01
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| Series: | JITeCS (Journal of Information Technology and Computer Science) |
| Online Access: | https://jitecs.ub.ac.id/index.php/jitecs/article/view/219 |
| _version_ | 1797248801462812672 |
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| author | M Syauqi Haris Tri Astoto Kurniawan Fatwa Ramdani |
| author_facet | M Syauqi Haris Tri Astoto Kurniawan Fatwa Ramdani |
| author_sort | M Syauqi Haris |
| collection | DOAJ |
| description |
Extractive Software Product Line Engineering (SPLE) puts features on the foremost aspect in domain analysis that needs to be extracted from the existing system's artifact. Feature in SPLE, which is closely related to system functionality, has been previously studied to be extracted from source code, models, and various text documents that exist along the software development process. Source code, with its concise and normative standard, has become the most focus target for feature extraction source on many kinds of research. However, in the software engineering principle, the Software Requirements Specification (SRS) document is the basis or main reference for system functionality conformance. Meanwhile, previous researches of feature extraction from text document are conducted on a list of functional requirement sentences that have been previously prepared, not literally SRS as a whole document. So, this research proposes direct processing on the SRS document that uses requirement boilerplates for requirement sentence statement. The proposed method uses Natural Language Processing (NLP) approach on the SRS document. Sequence Part-of-Speech (POS) tagging technique is used for automatic requirement sentence identification and extraction. The features are acquired afterward from extracted requirement sentences automatically using the word dependency parsing technique. Besides, mostly the previous researches about feature extraction were using non-public available SRS document that remains classified or not accessible, so this work uses selected SRS from publicly available SRS dataset to add reproducible research value. This research proves that requirement sentence extraction directly from the SRS document is viable with precision value from 64% to 100% and recall value from 64% to 89%. While features extraction from extracted requirement sentences has success rate from 65% to 88%.
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| first_indexed | 2024-04-24T20:20:22Z |
| format | Article |
| id | doaj.art-3391a53db4254efea86060130f4aefc5 |
| institution | Directory Open Access Journal |
| issn | 2540-9433 2540-9824 |
| language | English |
| last_indexed | 2024-04-24T20:20:22Z |
| publishDate | 2020-12-01 |
| publisher | University of Brawijaya |
| record_format | Article |
| series | JITeCS (Journal of Information Technology and Computer Science) |
| spelling | doaj.art-3391a53db4254efea86060130f4aefc52024-03-22T08:32:08ZengUniversity of BrawijayaJITeCS (Journal of Information Technology and Computer Science)2540-94332540-98242020-12-015310.25126/jitecs.202053219Automated Features Extraction from Software Requirements Specification (SRS) Documents as The Basis of Software Product Line (SPL) EngineeringM Syauqi Haris0Tri Astoto Kurniawan1Fatwa Ramdani2Brawijaya UniversityBrawijaya UniversityBrawijaya University Extractive Software Product Line Engineering (SPLE) puts features on the foremost aspect in domain analysis that needs to be extracted from the existing system's artifact. Feature in SPLE, which is closely related to system functionality, has been previously studied to be extracted from source code, models, and various text documents that exist along the software development process. Source code, with its concise and normative standard, has become the most focus target for feature extraction source on many kinds of research. However, in the software engineering principle, the Software Requirements Specification (SRS) document is the basis or main reference for system functionality conformance. Meanwhile, previous researches of feature extraction from text document are conducted on a list of functional requirement sentences that have been previously prepared, not literally SRS as a whole document. So, this research proposes direct processing on the SRS document that uses requirement boilerplates for requirement sentence statement. The proposed method uses Natural Language Processing (NLP) approach on the SRS document. Sequence Part-of-Speech (POS) tagging technique is used for automatic requirement sentence identification and extraction. The features are acquired afterward from extracted requirement sentences automatically using the word dependency parsing technique. Besides, mostly the previous researches about feature extraction were using non-public available SRS document that remains classified or not accessible, so this work uses selected SRS from publicly available SRS dataset to add reproducible research value. This research proves that requirement sentence extraction directly from the SRS document is viable with precision value from 64% to 100% and recall value from 64% to 89%. While features extraction from extracted requirement sentences has success rate from 65% to 88%. https://jitecs.ub.ac.id/index.php/jitecs/article/view/219 |
| spellingShingle | M Syauqi Haris Tri Astoto Kurniawan Fatwa Ramdani Automated Features Extraction from Software Requirements Specification (SRS) Documents as The Basis of Software Product Line (SPL) Engineering JITeCS (Journal of Information Technology and Computer Science) |
| title | Automated Features Extraction from Software Requirements Specification (SRS) Documents as The Basis of Software Product Line (SPL) Engineering |
| title_full | Automated Features Extraction from Software Requirements Specification (SRS) Documents as The Basis of Software Product Line (SPL) Engineering |
| title_fullStr | Automated Features Extraction from Software Requirements Specification (SRS) Documents as The Basis of Software Product Line (SPL) Engineering |
| title_full_unstemmed | Automated Features Extraction from Software Requirements Specification (SRS) Documents as The Basis of Software Product Line (SPL) Engineering |
| title_short | Automated Features Extraction from Software Requirements Specification (SRS) Documents as The Basis of Software Product Line (SPL) Engineering |
| title_sort | automated features extraction from software requirements specification srs documents as the basis of software product line spl engineering |
| url | https://jitecs.ub.ac.id/index.php/jitecs/article/view/219 |
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