AI-Based Cognitive Decision Support Framework for Resource-Optimized  Sustainable Software Testing in SMEs

Meghana R, Dr.Piyush Kumar Pareek

AI-Based Cognitive Decision Support Framework for Resource-Optimized Sustainable Software Testing in SMEs

Authors

Meghana R, Dr.Piyush Kumar Pareek

Keywords:

Sustainable software testing; small and medium enterprises (SMEs); Green-AI; cognitive decision support; test case prioritization; flakiness mitigation; energy-aware CI/CD; policy-as-code

Abstract

Small and medium-sized software enterprises (SMEs) are under pressure to deliver qualityquickly while operating with strict budget, talent, and infrastructure constraints. Testexecution—often the most compute-intensive

References

Schwartz, R., Dodge, J., Smith, N. A., Etzioni, O. “Green AI,” Commun. ACM, 63(12), 2020.

Pan, R., Bagherzadeh, M., Ghaleb, T. A., Briand, L. “Test Case Selection and Prioritization Using Machine Learning: A Systematic Literature Review,” Empirical Software Engineering, 2022.

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Published

2024-10-18

How to Cite

Meghana R, Dr.Piyush Kumar Pareek. (2024). AI-Based Cognitive Decision Support Framework for Resource-Optimized Sustainable Software Testing in SMEs. Journal of Computational Analysis and Applications (JoCAAA), 33(06), 2944–2949. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3751