Research Article
Intelligent Requirements Validation: An Empirical Evaluation of NLP Techniques for Automated Quality Assurance
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 187 - Issue 53 |
| Published: November 2025 |
| Authors: Yuliia Baranetska |
10.5120/ijca2025925909
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Yuliia Baranetska . Intelligent Requirements Validation: An Empirical Evaluation of NLP Techniques for Automated Quality Assurance. International Journal of Computer Applications. 187, 53 (November 2025), 58-66. DOI=10.5120/ijca2025925909
@article{ 10.5120/ijca2025925909,
author = { Yuliia Baranetska },
title = { Intelligent Requirements Validation: An Empirical Evaluation of NLP Techniques for Automated Quality Assurance },
journal = { International Journal of Computer Applications },
year = { 2025 },
volume = { 187 },
number = { 53 },
pages = { 58-66 },
doi = { 10.5120/ijca2025925909 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2025
%A Yuliia Baranetska
%T Intelligent Requirements Validation: An Empirical Evaluation of NLP Techniques for Automated Quality Assurance%T
%J International Journal of Computer Applications
%V 187
%N 53
%P 58-66
%R 10.5120/ijca2025925909
%I Foundation of Computer Science (FCS), NY, USA
Abstract
To ensure high-quality software at scale, faster and more reliable requirements validation is needed beyond manual methods. This paper examines the use of Natural Language Processing (NLP) for automated validation through a mixed-method study in the automotive and healthcare sectors. Manual validation was compared with an NLP-based approach on 50 requirements, assessing time, defect detection, and cost. The NLP method reduced validation time by 66.7%, identified 29.4% more defects, and lowered costs by 40%, with all differences being statistically significant. This paper discusses the workflow, dataset, annotation scheme (ambiguity, inconsistency, redundancy), implementation tools (spaCy, BERT, NLTK), and challenges (domain terminology, integration).
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