Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)

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Advancing Sustainable Quality Engineering: Preventative Test Approach with PreventativeTestPro GPT and Observability Data

Authors
Soham Patel1, Kailas Patil1, *, Vidula Meshram2
1Vishwakarma University, Survey No 2 3, 4, Kondhwa Main Rd, Laxmi Nagar, Betal Nagar, Kondhwa, Pune, Maharashtra, 411048, India
2Vishwakarma Institute of Technology, Upper Indira Nagar, Upper Indira Nagar, Bibwewadi, Pune, Maharashtra, 411037, India
*Corresponding author. Email: kailas.patil@vupune.ac.in
Corresponding Author
Kailas Patil
Available Online 6 January 2026.
DOI
10.2991/978-94-6463-948-3_29How to use a DOI?
Keywords
ChatGPT; LLM; Preventative Test; Test Prioritization
Abstract

The paper introduces a novel test prioritization and prevention testing method with the use of synthetic observability data, identified as logs, traces, and metrics. To this end, a PreventativeTestPro GPT and a Custom ChatGPT were used. The proposed method, according to the real-time analysis of the issue of the runtime, prioritizes the existing test cases, develops specific tests and recommends the mitigation strategies to eliminate the reoccurring of the problem. The inclusion of requirements and static code analysis is different to the traditional test generation tools. The solution involves a domain-tuned LLM that can detect test heuristics and observability artifacts. It is therefore cheaper and more scalable than the custom models used. The research is a good addition to AI-based software quality engineering, demonstrating that it can be of importance to both DevOps and SRE operations.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)
Series
Advances in Intelligent Systems Research
Publication Date
6 January 2026
ISBN
978-94-6463-948-3
ISSN
1951-6851
DOI
10.2991/978-94-6463-948-3_29How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Soham Patel
AU  - Kailas Patil
AU  - Vidula Meshram
PY  - 2026
DA  - 2026/01/06
TI  - Advancing Sustainable Quality Engineering: Preventative Test Approach with PreventativeTestPro GPT and Observability Data
BT  - Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)
PB  - Atlantis Press
SP  - 398
EP  - 418
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-948-3_29
DO  - 10.2991/978-94-6463-948-3_29
ID  - Patel2026
ER  -