ISSN2320-2882
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Paper Title

Modal Verb Based Software Requirements Prioritization through Classification - A Novel Approach Using Machine Learning and Natural Language Processing

Authors

Suchetha Vijayakumar , Suresha D

Keywords

Functional Requirement Prioritization, Modal Verbs, Machine Learning, Natural Language Processing, Requirement Engineering, TF-IDF Vectorization, Linear SVM, Classifier Comparison, Software Development, Automated Prioritization

Abstract

Effective and systematic prioritization of functional requirements is critical and crucial for successful software development, especially in complex projects. Most traditional methods often overlook the linguistic nuances of requirement specifications, such as modal verbs, which convey varying levels of priority. This study explores the integration of modal verb analysis with machine learning classifiers to automate the prioritization process. Functional requirements are classified into High, Medium, and Low priority levels based on the presence of modal verbs such as must, will, should, would, may, can, might. Using a dataset of 375 requirement descriptions from 25 different projects, we employed TF-IDF vectorization for feature extraction and evaluated various classifiers including Random Forest, Logistic Regression, Naive Bayes, and Linear SVM. Linear SVM emerged as the best-performing model, achieving 96% accuracy with superior precision, recall, and F1-score metrics. This work demonstrates the potential of Natural Language Processing features and Machine Learning to enhance requirement prioritization, making software development workflows more efficient and automated

How To Cite

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IJCRT — journal style
"Modal Verb Based Software Requirements Prioritization through Classification - A Novel Approach Using Machine Learning and Natural Language Processing", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.13, Issue 9, page no.e398-e405, September 2025, Available :https://ijcrt.org/papers/IJCRT2509506.pdf
APA — 7th edition
Vijayakumar, S., & D, S. (2025). Modal Verb Based Software Requirements Prioritization through Classification - A Novel Approach Using Machine Learning and Natural Language Processing. International Journal of Creative Research Thoughts, 13(9), e398-e405. https://doi.org/10.56975/ijcrt.v13i9.294123
MLA — 9th edition
Vijayakumar, Suchetha, and Suresha D. "Modal Verb Based Software Requirements Prioritization through Classification - A Novel Approach Using Machine Learning and Natural Language Processing." International Journal of Creative Research Thoughts, vol. 13, no. 9, 2025, pp. e398-e405, https://doi.org/10.56975/ijcrt.v13i9.294123.
Chicago — 17th, bibliography
Vijayakumar, Suchetha, and Suresha D. "Modal Verb Based Software Requirements Prioritization through Classification - A Novel Approach Using Machine Learning and Natural Language Processing." International Journal of Creative Research Thoughts 13, no. 9 (2025): e398-e405. https://doi.org/10.56975/ijcrt.v13i9.294123.
Harvard — author–date
Vijayakumar, S. and D, S. (2025) 'Modal Verb Based Software Requirements Prioritization through Classification - A Novel Approach Using Machine Learning and Natural Language Processing', International Journal of Creative Research Thoughts, 13(9), pp. e398-e405. Available at: https://doi.org/10.56975/ijcrt.v13i9.294123
IEEE — numbered reference
S. Vijayakumar and S. D, "Modal Verb Based Software Requirements Prioritization through Classification - A Novel Approach Using Machine Learning and Natural Language Processing," IJCRT, vol. 13, no. 9, pp. e398-e405, Sep. 2025, doi: 10.56975/ijcrt.v13i9.294123.
Vancouver — biomedical
Vijayakumar S, D S. Modal Verb Based Software Requirements Prioritization through Classification - A Novel Approach Using Machine Learning and Natural Language Processing. IJCRT. 2025 Sep;13(9):e398-e405. doi: 10.56975/ijcrt.v13i9.294123
AMA — 11th edition
Vijayakumar S, D S. Modal Verb Based Software Requirements Prioritization through Classification - A Novel Approach Using Machine Learning and Natural Language Processing. IJCRT. 2025;13(9):e398-e405. doi:10.56975/ijcrt.v13i9.294123
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2509506, author = {Suchetha Vijayakumar and Suresha D}, title = {Modal Verb Based Software Requirements Prioritization through Classification - A Novel Approach Using Machine Learning and Natural Language Processing}, journal = {International Journal of Creative Research Thoughts}, volume = {13}, number = {9}, pages = {e398-e405}, year = {2025}, month = {September}, issn = {2320-2882}, doi = {10.56975/ijcrt.v13i9.294123}, url = {https://doi.org/10.56975/ijcrt.v13i9.294123} }
RIS — EndNote, RefWorks
TY - JOUR AU - Vijayakumar, Suchetha AU - D, Suresha TI - Modal Verb Based Software Requirements Prioritization through Classification - A Novel Approach Using Machine Learning and Natural Language Processing T2 - International Journal of Creative Research Thoughts JA - IJCRT VL - 13 IS - 9 PY - 2025 SN - 2320-2882 DO - 10.56975/ijcrt.v13i9.294123 UR - https://doi.org/10.56975/ijcrt.v13i9.294123 SP - e398-e405 ER -

Issue

Volume 13 Issue 9, September-2025
Pages : e398-e405

Article Information

Pages
e398-e405
Published
September 2025
Registration ID
IJCRT_294123
Published Paper ID
IJCRT2509506
Research Area
Science and Technology
Author Type
Indian Author
Location
Dakshina kannada, Karnataka, India
Licence
CC BY 4.0 · Open Access
ISSN & Impact Factor
2320-2882 · IF 9.17
Downloads
339
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International Journal of Creative Research Thoughts Published by IJCRT Publication
2320-2882 ISSN
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© 2025 — Authors hold the copyright of this article. This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
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Declarations

Funding

No external funding was received for this study.

Conflict of Interest

The authors declare that they have no conflict of interest.

Acknowledgements

The authors would like to thank the reviewers and the editorial board of International Journal of Creative Research Thoughts for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.

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