Ethical AI-Powered Regression Test Selection

Autor: Mirgita Frasheri, Per Erik Strandberg, Eduard Paul Enoiu
Rok vydání: 2021
Předmět:
Zdroj: AITest
Strandberg, P E, Frasheri, M & Enoiu, E P 2021, Ethical AI-Powered Regression Test Selection . in 2021 IEEE International Conference on Artificial Intelligence Testing (AITest) . IEEE, pp. 83-84, 3rd IEEE International Conference on Artificial Intelligence Testing, AITest 2021, Virtual, Online, United Kingdom, 23/08/2021 . https://doi.org/10.1109/AITEST52744.2021.00025
International Conference On Artificial Intelligence Testing
2021 IEEE International Conference on Artificial Intelligence Testing (AITest)
DOI: 10.48550/arxiv.2106.16050
Popis: Test automation is common in software development; often one tests repeatedly to identify regressions. If the amount of test cases is large, one may select a subset and only use the most important test cases. The regression test selection (RTS) could be automated and enhanced with Artificial Intelligence (AI-RTS). This however could introduce ethical challenges. While such challenges in AI are in general well studied, there is a gap with respect to ethical AI-RTS. By exploring the literature and learning from our experiences of developing an industry AI-RTS tool, we contribute to the literature by identifying three challenges (assigning responsibility, bias in decision-making and lack of participation) and three approaches (explicability, supervision and diversity). Additionally, we provide a checklist for ethical AI-RTS to help guide the decision-making of the stakeholders involved in the process.
Comment: 2 pages, 1 figure, accepted to AITest'21
Databáze: OpenAIRE