Aiming at the problem of insufficient consideration of skill rarity and worker skill coverage in the task allocation decision of the current software crowdsourcing platform, this paper proposes a task priority-based software crowdsourcing allocation algorithm. First, the skill rarity is calculated based on the tasks to be assigned and the development skills of workers, and the task priority is determined accordingly. Then, the pre-allocation scheme based on the priority is used as the initial input of the allocation algorithm. Finally, the parameters of the algorithm are set based on the global optimization objectives of maximizing the number of tasks to be assigned and minimizing the number of workers to complete the crowdsourcing task allocation. The experimental results show that compared with allocation algorithms such as candidate task worker group algorithm based on allocation utility and preference matching satisfaction maximization, The algorithms in this paper improves the number of successful task allocations and average worker overhead by 15.23% and 12.76% on average.