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Parallel testing technology can simultaneously test multiple tasks, improve resource utilization, and save testing costs; Parallel test scheduling problem is a complex combinatorial optimization problem, and it is the core element of parallel test technology; As the carrier of parallel testing technology, the performance and solving efficiency of parallel testing systems are particularly important; The limit theorem of parallel test completion time is studied, the mathematical model of parallel test task scheduling is established, and the shortcomings of traditional meta heuristic algorithms for solving parallel test problems are analyzed. A hybrid artificial bee colony algorithm based on the combination of recursive search technology of dynamic programming and artificial bee colony algorithm is proposed, and the hybrid artificial bee colony algorithm is verified by using the precise algorithm of Integer programming and genetic algorithm; The conclusion is that using hybrid artificial bee colony algorithm for scheduling parallel testing tasks saves nearly 50% of time, reduces about 20% of hardware resource usage, improves testing efficiency, and can meet practical engineering applications.