Multi-Objective Regression Test Selection

Regression testing is challenging, yet essential, for maintaining evolving complex soft- ware. Efficient regression that minimizes the time and maximizes detection of faults in great demand fast-paced software develop- ment. Many research studies have been proposed selecting tests under a constraint. This paper presents new approach first evaluates fault detectability each test based on extent to which impacted by changes. Then, two optimization algorithms are optimize multi-objective function takes execution as inputs select an optimal subset can detect maximal given The validity efficacy were evaluated using empirical industrial systems. promising results suggest has potential ensure quality