Fault-Propagation Analysis: Unveiling Equivalence in Software Mutation Testing

Efficiently unraveling equivalent mutants in software mutation testing is a critical endeavor for enhancing testing efficacy and resource utilization. This paper presents a pioneering approach that integrating advanced optimization methods into the fault-propagation analysis framework. The objective is to augment the precision and computational efficiency of identifying equivalent mutants, a pivotal aspect of robust software testing.Our methodology incorporates optimization techniques into the fault-propagation analysis of program instructions, enabling a more streamlined and targeted exploration of the mutation space. By strategically optimizing the analysis process, we aim to accelerate the identification of equivalent mutants while maintaining a high level of accuracy. The proposed approach is substantiated through rigorous experimentation across diverse software systems, showcasing its ability to outperform traditional methods in terms of both speed and precision. This paper contributes a novel perspective to the realm of mutation testing, emphasizing the integration of optimization methods to refine fault-propagation analysis. The results not only validate the effectiveness of the optimized approach but also underscore its potential to revolutionize mutation testing practices. The insights gained from this research pave the way for a more efficient and sophisticated approach to software mutation testing, emphasizing the crucial role of optimization in enhancing the identification of equivalent mutants.