计算机应用 ›› 2019, Vol. 39 ›› Issue (2): 528-533.DOI: 10.11772/j.issn.1001-9081.2018061309

• 计算机软件技术 • 上一篇    下一篇

基于活跃时间分组的软件众包工人选择机制

周壮1, 余敦辉1,2, 张万山1,2, 王意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中心, 武汉 430062
  • 收稿日期:2018-06-25 修回日期:2018-08-09 出版日期:2019-02-10 发布日期:2019-02-15
  • 通讯作者: 张万山
  • 作者简介:周壮(1994-),男,湖北天门人,硕士研究生,主要研究方向:软件众包;余敦辉(1974-),男,湖北武汉人,副教授,博士,CCF会员,主要研究方向:服务计算、大数据;张万山(1973-),男,湖北武汉人,讲师,硕士,主要研究方向:Web信息挖掘;王意(1992-),男,湖北武汉人,硕士研究生,主要研究方向:大数据。
  • 基金资助:
    国家973计划项目(2014CB340404);国家自然科学基金资助项目(61572371,61702377)。

Software crowdsourcing worker selection mechanism based on active time grouping

ZHOU Zhuang1, YU Dunhui1,2, ZHANG Wanshan1,2, WANG Yi1   

  1. 1. School of Computer Science and Information Engineering, Hubei University, Wuhan Hubei 430062, China;
    2. Education Informationization Engineering and Technology Center, Wuhan Hubei 430062, China
  • Received:2018-06-25 Revised:2018-08-09 Online:2019-02-10 Published:2019-02-15
  • Supported by:
    This work is partially supported by the National Key R&D Program of China (2014CB340404), the National Natural Science Foundation of China (61572371, 61702377).

摘要: 针对现有的软件众包工人选择机制对工人间协同开发考虑不足的问题,在竞标模式的基础上提出一种基于活跃时间分组的软件众包工人选择机制。首先,基于活跃时间将众包工人划分为多个协同开发组;然后,根据组内工人开发能力和协同因子计算协同工作组权重;最后,选定权重最大的协同工作组为最优工作组,并根据模块复杂度为每个任务模块从该组内选择最适合的工人。实验结果表明,该机制相比能力优先选择方法在工人平均能力上仅有0.57%的差距,同时因为保证了工人间的协同而使项目风险平均降低了32%,能有效指导需多人协同进行的众包软件任务的工人选择。

关键词: 软件众包, 协同开发, 众包工人选择机制, 协同工作组, 活跃时间

Abstract: Concerning the problem that existing software crowdsourcing worker selection mechanisms do not consider the collaboration among workers, a crowdsourcing worker selection mechanism with bidding model based on active time grouping was proposed. Firstly, crowd-sourced workers were divided into multiple collaborative working groups based on active time. Then, the weights of the working groups were calculated according to the development capabilities of the workers in the group and collaboration factors. Finally, the collaborative working group with the highest weight was selected as the optimal working group, and the most suitable worker from this group was selected for each task module according to the complexity of the module. The experimental results show that the proposed mechanism has a gap of only 0.57% in the average worker ability compared to the ability only allocation method. At the same time, it reduces the project risk by an average of 32% due to the ensurence of the cooperation between workers, which can effectively guide the selection of workers for multi-person collaborative crowdsourcing software tasks.

Key words: software crowdsourcing, collaborative development, crowdsourcing workers selection mechanism, collaborative working group, active time

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