计算机工程 ›› 2019, Vol. 45 ›› Issue (8): 120-124,134.doi: 10.19678/j.issn.1000-3428.0053485

• 体系结构与软件技术 • 上一篇    下一篇

基于动态解耦的软件众包任务分解算法

王晨旭1, 王晓晨1, 余敦辉1,2, 吴珊1   

  1. 1. 湖北大学 计算机与信息工程学院, 武汉 430062;
    2. 湖北省教育信息化工程技术研究中心, 武汉 430062
  • 收稿日期:2018-12-25 修回日期:2019-02-14 出版日期:2019-08-15 发布日期:2019-08-08
  • 作者简介:王晨旭(1997-),男,本科生,主研方向为软件众包模式、服务计算;王晓晨,本科生;余敦辉(通信作者),副教授、博士;吴珊,本科生。
  • 基金项目:
    国家自然科学基金(61572371,61832014);湖北省技术创新专项(2018ACA13)。

Software Crowdsourcing Task Decomposition Algorithm Based on Dynamic Decoupling

WANG Chenxu1, WANG Xiaochen1, YU Dunhui1,2, WU Shan1   

  1. 1. College of Computer Science and Information Engineering, Hubei University, Wuhan 430062, China;
    2. Hubei Province Engineering Technology Research Center for Education Informationization, Wuhan 430062, China
  • Received:2018-12-25 Revised:2019-02-14 Online:2019-08-15 Published:2019-08-08

摘要: 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。

关键词: 软件众包, 任务分解, 任务粒度, 动态解耦, 设计结构矩阵

Abstract: 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.

Key words: software crowdsourcing, task decomposition, task granularity, dynamic decoupling, Design Structure Matrix(DSM)

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