Abstract
Regression Test Suite Optimization (RTO) is an active research area. A Regression Test Suite is always growing due to changes in software, which increases testing time. To save time and resources optimization of regression test suites is mandatory. Researchers have optimized test suites using conventional and Computational Intelligence based approaches and achieve optimization of regression test suites through selection techniques, minimization or reduction techniques and ranking or prioritization techniques. This paper surveys existing techniques for regression test suite optimization, various tools and mathematical models being used for RTO. During this survey we found many interesting facts about regression test suite optimization that will be shared in the conclusion.
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Index Terms
- Exploration and analysis of regression test suite optimization
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