A Novel Algorithm For Generating Hard-To-Kill Higher Order Mutants Using Chemical Reaction Optimization

In the field of software engineering, ensuring the reliability and robustness of software is paramount, and software testing plays a critical role in this process. Mutation testing, a fault-based technique, evaluates the effectiveness of test suites by introducing artificial defects, known as mutants, into programs. This research presents a novel method for generating higher-order mutants (HOMs) using the Chemical Reaction Optimization (CRO) algorithm, which enhances the rigor of mutation testing by creating harder-to-detect mutants. The CRO algorithm employs four types of collision operators: on-wall ineffective, synthesis, decomposition, and inter-molecular ineffective, to modify mutants and simulate complex faults. Through experimentation with iterations set at 10, 30, and 50, it was found that increasing the number of iterations significantly reduces the number of mutants and increases their detection difficulty. Notably, with 50 iterations, the approach achieved a 93% reduction in mutants and lowered the mutation score to 27.77%, demonstrating the robustness of the generated mutants. The research further introduces the HOMUsingCRO tool, which automates the mutant generation and testing process, generating XML-based reports for effective mutant analysis. The proposed approach outperforms existing techniques in both mutant reduction and mutation score, offering a more comprehensive solution for improving software test suite effectiveness.