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Intelligent Requirements Validation: An Empirical Evaluation of NLP Techniques for Automated Quality Assurance
by
Yuliia Baranetska
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 53 |
| Year of Publication: 2025 |
| Authors: Yuliia Baranetska |
10.5120/ijca2025925909
|
Yuliia Baranetska . Intelligent Requirements Validation: An Empirical Evaluation of NLP Techniques for Automated Quality Assurance. International Journal of Computer Applications. 187, 53 ( Nov 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
},
issue_date = { Nov 2025 },
volume = { 187 },
number = { 53 },
month = { Nov },
year = { 2025 },
issn = { 0975-8887 },
pages = {
58-66
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume187/number53/intelligent-requirements-validation-an-empirical-evaluation-of-nlp-techniques-for-automated-quality-assurance/
},
doi = { 10.5120/ijca2025925909 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-11-18T21:10:40.414246+05:30
%A Yuliia Baranetska
%T Intelligent Requirements Validation: An Empirical Evaluation of NLP Techniques for Automated Quality Assurance
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 53
%P 58-66
%D 2025
%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).
References
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Index Terms
Computer Science
Information Sciences
Keywords