Cognitive AI-Driven Decision Support for Sustainable and Resource Efficient Software Testing in Small and Medium Enterprises

Meghana R,Dr.Piyush Kumar Pareek

Cognitive AI-Driven Decision Support for Sustainable and Resource Efficient Software Testing in Small and Medium Enterprises

Authors

Meghana R,Dr.Piyush Kumar Pareek

Keywords:

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

Abstract

Software testing is indispensable for quality assurance, yet in small and medium enterprises(SMEs) it frequently becomes the most time- and compute-intensive phase of delivery, inflatingcosts, energy use, and time-to-market.

References

Schwartz, R., Dodge, J., Smith, N. A., Etzioni, O., “Green AI,” Communications of the 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

2024-11-20

How to Cite

Meghana R,Dr.Piyush Kumar Pareek. (2024). Cognitive AI-Driven Decision Support for Sustainable and Resource Efficient Software Testing in Small and Medium Enterprises . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 6377–6382. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3750