Fuzzy Inference System for Test Case Prioritization in Software Testing
<|reference_start|>Fuzzy Inference System for Test Case Prioritization in Software Testing: In the realm of software development, testing is crucial for ensuring software quality and adherence to requirements. However, it can be time-consuming and resource-intensive, especially when dealing with large and complex software systems. Test case prioritization (TCP) is a vital strategy to enhance testing efficiency by identifying the most critical test cases for early execution. This paper introduces a novel fuzzy logic-based approach to automate TCP, using fuzzy linguistic variables and expert-derived fuzzy rules to establish a link between test case characteristics and their prioritization. Our methodology utilizes two fuzzy variables - failure rate and execution time - alongside two crisp parameters: Prerequisite Test Case and Recently Updated Flag. Our findings demonstrate the proposed system capacity to rank test cases effectively through experimental validation on a real-world software system. The results affirm the practical applicability of our approach in optimizing the TCP and reducing the resource intensity of software testing.<|reference_end|>
@article{karatayev2024fuzzy,
    title={Fuzzy Inference System for Test Case Prioritization in Software Testing},
    author={Aron Karatayev, Anna Ogorodova, Pakizar Shamoi},
    journal={arXiv preprint arXiv:2404.16395},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.16395},
    primaryClass={cs.SE cs.AI}
}