Abstract: The existing software crowdsourcing platforms do not consider the ability of workers adequately, which leads to the low completion quality of tasks assigned to workers. In order to solve the problem, a new Ability Dynamic Measurement algorithm (ADM) for software crowdsourcing workers was proposed to achieve the dynamic measurement of the workers' ability. Firstly, the initial ability of a worker was calculated based on his static skill coverage rate. Secondly, for the single task completed by the worker in history, task complexity, task completion quality, and task development timeliness were integrated to realize the calculation of development ability, and the development ability decaying with time was calculated according to a time factor. Then, according to the time sequence of all the completed tasks in history, the dynamic update of ability measurement value was realized. Finally, the development ability of the worker for a task to be assigned was calculated based on the skill coverage rates of historical tasks. The experimental results show that, compared with the user reliability measurement algorithm, the proposed ability dynamic measurement algorithm has a better rationality and effectiveness, and the average coincidence degree of ability measurement is up to 90.5%, which can effectively guide task assignment.

Key words: software crowdsourcing, ability measurement, dynamic update, task assignment, software complexity

摘要： 针对现有软件众包平台对工人能力考虑不足，导致分配给工人的任务完成质量低下的问题，提出了一种软件众包工人能力动态度量算法（ADM），实现工人能力的动态度量。首先，基于静态技能覆盖率，实现工人初始能力的计算；其次，对于工人历史完成的单个任务，综合任务复杂度、任务完成质量及任务开发时效，实现开发能力的计算，并根据时间因子计算随时间衰减的开发能力；然后，根据所有历史完成任务的时间先后顺序，实现能力度量值的动态更新；最后，基于历史任务技能覆盖率，计算工人对于待分配任务的开发能力。实验结果表明，与用户可靠性度量算法相比，所提出的能力动态度量算法具有较好的合理性与有效性，使能力度量吻合度平均值最高达到90.5%，能有效指导任务分配。

关键词: 软件众包, 能力度量, 动态更新, 任务分配, 软件复杂度