Trends in SDLC Document Review using Generative AI

Authors

  • Prashant Gulave Department of Computer Science, JSPM’s Rajarshi Shahu College of Engineering, Pune, Maharashtra, India Author
  • Dr. Kavita Moholkar Department of Computer Science, JSPM’s Rajarshi Shahu College of Engineering, Pune, Maharashtra, India Author

DOI:

https://doi.org/10.32628/CSEIT25112777

Keywords:

Generative AI, SDLC, Document Review, Large Language Models, NLP

Abstract

This research paper explores the evolving role of Generative AI in Software Development Life Cycle (SDLC) document review. With AI-driven advancements in Natural Language Processing (NLP), models such as GPT, BERT, and domain-specific LLMs have been adapted to evaluate requirement specifications, test plans, and design documents. We present an analysis of how these models are being fine-tuned for document validation, compliance checking, and contextual feedback generation in the software industry. The paper also examines the integration of rule-based methods with AI, providing structured feedback for engineering domain documentation. Furthermore, we discuss emerging trends, challenges, and future research directions for enhancing AI-based document review in SDLC.

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References

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Published

02-04-2025

Issue

Vol. 11 No. 2 (2025): March-April

Section

Research Articles

License

Copyright (c) 2025 International Journal of Scientific Research in Computer Science, Engineering and Information Technology

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Prashant Gulave and Dr. Kavita Moholkar, “Trends in SDLC Document Review using Generative AI”, Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, vol. 11, no. 2, pp. 3009–3011, Apr. 2025, doi: 10.32628/CSEIT25112777.