Prioritization of Modules to Reduce Software Testing Time and Costs Using Evolutionary Algorithms and the KLOC Method

Research in software testing is essential due to its critical role in the Software Development Life Cycle (SDLC), often consuming up to 50% of development costs. This study focuses on optimizing testing processes to reduce time and costs while maintaining quality. Using a KLOC-based approach, genetic algorithms, and evolutionary techniques, the research prioritizes modules by assigning testing time based on importance, ensuring efficient testing of critical components. Applicable to maintenance, development, and reengineering projects, this model enhances cost efficiency and consistency. The findings emphasize the need for innovative methodologies in software testing to improve precision, reduce errors, and manage resources effectively.