TY - GEN
T1 - Automated requirement sentences extraction from software requirement specification document
AU - Haris, M. Syauqi
AU - Kurniawan, Tri Astoto
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/11/16
Y1 - 2020/11/16
N2 - In the requirement reuse and natural language document-based Software Product Line (SPL) domain analysis, requirement sentences of the requirement document are the primary concern. Most studies conducted in this research area have document preprocessing stage in their methods that is a manual process to separate requirement sentences and non-requirement sentences from the document. This manual labor process might be tedious and error-prone since it will need much time and expert intervention to make this process completely done. In this paper, we present a method to automate requirement sentence extraction from the Software Requirement Specification (SRS) document by leveraging Natural Language Processing (NLP) approach and requirement boilerplate sentence patterns. Conducted experiments in this research show this method has such accuracy from 64% to 100% on precision value and recall value in the range of 64% to 89%.
AB - In the requirement reuse and natural language document-based Software Product Line (SPL) domain analysis, requirement sentences of the requirement document are the primary concern. Most studies conducted in this research area have document preprocessing stage in their methods that is a manual process to separate requirement sentences and non-requirement sentences from the document. This manual labor process might be tedious and error-prone since it will need much time and expert intervention to make this process completely done. In this paper, we present a method to automate requirement sentence extraction from the Software Requirement Specification (SRS) document by leveraging Natural Language Processing (NLP) approach and requirement boilerplate sentence patterns. Conducted experiments in this research show this method has such accuracy from 64% to 100% on precision value and recall value in the range of 64% to 89%.
KW - domain analysis
KW - natural language processing
KW - requirement boilerplate
KW - software product line
KW - software requirement reuse
UR - https://www.scopus.com/pages/publications/85099014527
U2 - 10.1145/3427423.3427450
DO - 10.1145/3427423.3427450
M3 - Conference contribution
AN - SCOPUS:85099014527
T3 - ACM International Conference Proceeding Series
SP - 142
EP - 147
BT - Proceedings of 2020 International Conference on Sustainable Information Engineering and Technology, SIET 2020
PB - Association for Computing Machinery
T2 - 5th International Conference on Sustainable Information Engineering and Technology, SIET 2020
Y2 - 16 November 2020 through 17 November 2020
ER -