基于动态解耦的软件众包任务分解算法

Software Crowdsourcing Task Decomposition Algorithm Based on Dynamic Decoupling

综合考虑任务粒度与解耦水平,提出一种改进的软件众包任务分解算法。基于任务网络内的依赖关系计算任务粒度,根据各子任务在设计结构矩阵中的分布情况衡量解耦水平,并通过动态解耦进行软件众包任务分解。实验结果表明,与基于独立水平和传播成本的任务分解算法相比,该算法风险判定值和缺陷密度分别提升 0.244 0、 0.362 6、0.014 6、0.319 4,可保证软件众包任务完成质量。

Considering the task granularity and Decoupling Level(DL),an improved software crowdsourcing task decomposition algorithm is proposed.The task granularity is calculated based on the dependency relationship in the task network.The decoupling level is measured according to the distribution of each subtask in the Design Structure Matrix(DSM),and the software crowdsourcing task decomposition is performed by dynamic decoupling.Experimental results show that compared with the task decomposition algorithm based on Independent Level(IL) and Propagation Cost(PC),the risk judgment value and defect density of the algorithm are increased by 0.244 0,0.362 6,0.014 6 and 0.319 4 respectively,which can ensure the completion quality of software crowdsourcing tasks.