Extracting features from online software reviews to aid requirements reuse

Sets of common features are essential assets to be reused in fulfilling specific needs in software product line methodology. In Requirements Reuse (RR), the extraction of software features from Software Require- ment Specifications (SRS) is viable only to practitioners who have access to these softw...

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Main Authors:	Bakar, Noor Hasrina, M. Kasirun, Zarinah, Salleh, Norsaremah, A. Jalab, Hamid
Format:	Article
Language:	English English English
Published:	Elsevier B.V 2016
Subjects:	Q Science (General)
Online Access:	http://irep.iium.edu.my/54542/ http://irep.iium.edu.my/54542/ http://irep.iium.edu.my/54542/7/ASOC%20paper.pdf http://irep.iium.edu.my/54542/13/54542_Extracting%20features%20from%20online%20software%20reviews%20to%20aid%20requirements%20reuse_SCOPUS.pdf http://irep.iium.edu.my/54542/14/54542_Extracting%20features%20from%20online%20software%20reviews%20to%20aid%20requirements%20reuse_WoS.pdf

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recordtype	eprints
spelling	iium-545422017-07-14T02:00:17Z http://irep.iium.edu.my/54542/ Extracting features from online software reviews to aid requirements reuse Bakar, Noor Hasrina M. Kasirun, Zarinah Salleh, Norsaremah A. Jalab, Hamid Q Science (General) Sets of common features are essential assets to be reused in fulfilling specific needs in software product line methodology. In Requirements Reuse (RR), the extraction of software features from Software Require- ment Specifications (SRS) is viable only to practitioners who have access to these software artefacts. Due to organisational privacy, SRS are always kept confidential and not easily available to the public. As alter- natives, researchers opted to use the publicly available software descriptions such as product brochures and online software descriptions to identify potential software features to initiate the RR process. The aim of this paper is to propose a semi-automated approach, known as Feature Extraction for Reuse of Natural Language requirements (FENL), to extract phrases that can represent software features from soft- ware reviews in the absence of SRS as a way to initiate the RR process. FENL is composed of four stages, which depend on keyword occurrences from several combinations of nouns, verbs, and/or adjectives. In the experiment conducted, phrases that could reflect software features, which reside within online soft- ware reviews were extracted by utilising the techniques from information retrieval (IR) area. As a way to demonstrate the feature groupings phase, a semi-automated approach to group the extracted features were then conducted with the assistance of a modified word overlap algorithm. As for the evaluation, the proposed extraction approach is evaluated through experiments against the truth data set created man- ually. The performance results obtained from the feature extraction phase indicates that the proposed approach performed comparably with related works in terms of recall, precision, and F-Measure. Elsevier B.V 2016 Article PeerReviewed application/pdf en http://irep.iium.edu.my/54542/7/ASOC%20paper.pdf application/pdf en http://irep.iium.edu.my/54542/13/54542_Extracting%20features%20from%20online%20software%20reviews%20to%20aid%20requirements%20reuse_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/54542/14/54542_Extracting%20features%20from%20online%20software%20reviews%20to%20aid%20requirements%20reuse_WoS.pdf Bakar, Noor Hasrina and M. Kasirun, Zarinah and Salleh, Norsaremah and A. Jalab, Hamid (2016) Extracting features from online software reviews to aid requirements reuse. Applied Soft Computing, 49. pp. 1297-1315. ISSN 1568-4946 http://www.sciencedirect.com/science/article/pii/S1568494616303830
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English English
topic	Q Science (General)
spellingShingle	Q Science (General) Bakar, Noor Hasrina M. Kasirun, Zarinah Salleh, Norsaremah A. Jalab, Hamid Extracting features from online software reviews to aid requirements reuse
description	Sets of common features are essential assets to be reused in fulfilling specific needs in software product line methodology. In Requirements Reuse (RR), the extraction of software features from Software Require- ment Specifications (SRS) is viable only to practitioners who have access to these software artefacts. Due to organisational privacy, SRS are always kept confidential and not easily available to the public. As alter- natives, researchers opted to use the publicly available software descriptions such as product brochures and online software descriptions to identify potential software features to initiate the RR process. The aim of this paper is to propose a semi-automated approach, known as Feature Extraction for Reuse of Natural Language requirements (FENL), to extract phrases that can represent software features from soft- ware reviews in the absence of SRS as a way to initiate the RR process. FENL is composed of four stages, which depend on keyword occurrences from several combinations of nouns, verbs, and/or adjectives. In the experiment conducted, phrases that could reflect software features, which reside within online soft- ware reviews were extracted by utilising the techniques from information retrieval (IR) area. As a way to demonstrate the feature groupings phase, a semi-automated approach to group the extracted features were then conducted with the assistance of a modified word overlap algorithm. As for the evaluation, the proposed extraction approach is evaluated through experiments against the truth data set created man- ually. The performance results obtained from the feature extraction phase indicates that the proposed approach performed comparably with related works in terms of recall, precision, and F-Measure.
format	Article
author	Bakar, Noor Hasrina M. Kasirun, Zarinah Salleh, Norsaremah A. Jalab, Hamid
author_facet	Bakar, Noor Hasrina M. Kasirun, Zarinah Salleh, Norsaremah A. Jalab, Hamid
author_sort	Bakar, Noor Hasrina
title	Extracting features from online software reviews to aid requirements reuse
title_short	Extracting features from online software reviews to aid requirements reuse
title_full	Extracting features from online software reviews to aid requirements reuse
title_fullStr	Extracting features from online software reviews to aid requirements reuse
title_full_unstemmed	Extracting features from online software reviews to aid requirements reuse
title_sort	extracting features from online software reviews to aid requirements reuse
publisher	Elsevier B.V
publishDate	2016
url	http://irep.iium.edu.my/54542/ http://irep.iium.edu.my/54542/ http://irep.iium.edu.my/54542/7/ASOC%20paper.pdf http://irep.iium.edu.my/54542/13/54542_Extracting%20features%20from%20online%20software%20reviews%20to%20aid%20requirements%20reuse_SCOPUS.pdf http://irep.iium.edu.my/54542/14/54542_Extracting%20features%20from%20online%20software%20reviews%20to%20aid%20requirements%20reuse_WoS.pdf
first_indexed	2023-09-18T21:17:11Z
last_indexed	2023-09-18T21:17:11Z
_version_	1777411640521654272

Extracting features from online software reviews to aid requirements reuse

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