Optimization and Application of Task Scheduling in Virtual Testing Platforms

Virtual testing platforms offer cost-effective and user-friendly solutions for constructing environments for software testing. When utilized for software testing, the platforms face the challenge of efficiently allocating tasks under the constraints of limited resources and testing requirements, aiming to minimize the completion time of tasks. This paper addresses the challenges of resource conflicts, task priorities, task dependencies, and resource occupancy in software testing by developing an automated testing task scheduling model, introducing an improved jellyfish search algorithm (IJSA). This algorithm reasonably arranges the sequence of testing task steps under these constraints to minimize testing time. Integrating partition search and Levy flight strategies enhances its global search capabilities. Compared to other metaheuristic algorithms, simulation experiments demonstrate significant advantages in solution accuracy of this algorithm. Its application in a virtual testing platform proves the algorithm’s ability to determine the optimal task scheduling scheme more stably and effectively.