The Transforming Requirement Sentences in The Form of Requirement Boilerplates to Ontology Using Natural Language Processing

Requirements sentences in the software development process should be consistent. If there is inconsistency, there must be a conflict between requirements in a software project. We propose converting a requirement sentence into an ontology to check such inconsistency. Our approach separates each noun and verb in a requirements sentence using Natural Language Processing (NLP) technique to find concepts (nouns) and relations (verbs) between words. Our proposed ontology structure can be dynamically updated based on changes in the requirements sentences. We validated such an approach using precision and recall testing based on four requirements sentences with three times changes on four requirements sentences. The accuracy results are 100%. It means our approach can accommodate any changes in the requirements.

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Publication Details

Journal
Journal of Information Technology and Computer Science
Published
2025-09-01
DOI
https://doi.org/10.25126/jitecs.2025102535
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

The Transforming Requirement Sentences in The Form of Requirement Boilerplates to Ontology Using Natural Language Processing

Sabriansyah Rizqika Akbar, Muhammad Farabi Ismail, Tri Astoto Kurniawan
Journal of Information Technology and Computer Science
Big Data and Business Intelligence
article

The Transforming Requirement Sentences in The Form of Requirement Boilerplates to Ontology Using Natural Language Processing

Sabriansyah Rizqika Akbar, Muhammad Farabi Ismail, Tri Astoto Kurniawan
article en

Abstract

Requirements sentences in the software development process should be consistent. If there is inconsistency, there must be a conflict between requirements in a software project. We propose converting a requirement sentence into an ontology to check such inconsistency. Our approach separates each noun and verb in a requirements sentence using Natural Language Processing (NLP) technique to find concepts (nouns) and relations (verbs) between words. Our proposed ontology structure can be dynamically updated based on changes in the requirements sentences. We validated such an approach using precision and recall testing based on four requirements sentences with three times changes on four requirements sentences. The accuracy results are 100%. It means our approach can accommodate any changes in the requirements.

Journal of Information Technology and Computer ScienceVol. 10(2)
University of Brawijaya (ID)
Openalex Percentile: Top 62%
Big Data and Business Intelligence
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