Test Case Prioritization Using Dragon Boat Optimization for Software Quality Testing

Test Case Prioritization (TCP) is critical in software quality testing, aiming to identify high-priority test cases early in the testing process. This study proposes a novel TCP approach using the Dragon Boat Optimization Algorithm (DBOA), inspired by the synchronized teamwork seen in dragon boat racing. The proposed TCP-DBOA model strategically reorders test cases to improve fault detection efficiency while minimizing execution time. By using the Average Percentage of Faults Detected (APFD) as the optimization objective, the model enhances both coverage speed and testing effectiveness. DBOA offers advantages in handling large search spaces, balancing exploration and exploitation, and adapting to complex testing scenarios. The performance of TCP-DBOA is evaluated using four benchmark datasets—GZIP, GREP, TCAS, and CS-TCAS—demonstrating superior APFD values compared to existing methods. Results confirm the model’s robustness in reducing test execution time and improving fault detection early in the test cycle. This approach contributes to faster, more efficient regression testing, especially in continuous integration environments.