A Review of a Randomized Approach to Test Case Generation Using Genetic Algorithms

The quality of software relies on testing in accordance with user specifications and requirements. Designing, prioritizing, and optimizing test cases to ensure quality presents significant challenges. Various testing tools are available for software testing, applicable in both manual and automated contexts. Recent studies have demonstrated that automated software testing outperforms manual testing when employing heuristic search methods. This paper presents a survey on the genetic algorithm approach for the random generation of test cases in functional software testing.