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Who should make decision on this pull request? Analyzing time-decaying relationships and file similarities for integrator prediction

机译:谁应该在这个拉申请做出决定?分析积分器预测的时间衰减关系和文件相似性

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摘要

In pull-based development model, integrators are responsible for making decisions about whether to accept pull requests and integrate code contributions. Ideally, pull requests are assigned to integrators and evaluated within a short time after their submissions. However, the volume of incoming pull requests is large in popular projects, and integrators often encounter difficulties in processing pull requests in a timely fashion. Therefore, an automatic integrator prediction approach is required to assign appropriate pull requests to integrators. In this paper, we propose an approach TRFPre which analyzes Time-decaying Relationships and File similarities to predict integrators. We evaluate the effectiveness of TRFPre on 24 projects containing 138,373 pull requests. Experimental results show that TRFPre makes accurate integrator predictions in terms of accuracies and Mean Reciprocal Rank. Less than 2 predictions are needed to find correct integrator in 91.67% of projects. In comparison with state-of-the-art approaches cHRev, WRC, TIE, CoreDevRec and ACRec, TRFPre improves top-1 accuracy by 68.2%, 73.9%, 49.3%, 14.3% and 46.4% on average across 24 projects. (C) 2019 Elsevier Inc. All rights reserved.
机译:在基于拉动的发展模型中,集成商负责制定关于是否接受拉拔请求并集成代码贡献的决定。理想情况下,将拉出请求分配给集成商,并在其提交后的短时间内评估。然而,流行项目中的传入请求的体积很大,集成商经常在及时加工拉出请求时遇到困难。因此,需要自动积分器预测方法将适当的拉拔请求分配给集成商。在本文中,我们提出了一种方法TRFPRE,其分析了时间腐朽的关系和文件相似之处,以预测集成商。我们评估TRFPRE对包含138,373拉出请求的24个项目的有效性。实验结果表明,TRFPRE在准确性和平均互级别等级方面做出准确的集成商预测。在91.67%的项目中找到正确的集成商需要少于2个预测。与最先进的方法相比,Chrev,WRC,Tie,CoreDevrec和Acrec,TRFPRE在24个项目中平均提高了68.2%,73.9%,49.3%,14.3%,14.3%和46.4%。 (c)2019 Elsevier Inc.保留所有权利。

著录项

  • 来源
    《The Journal of Systems and Software》 |2019年第8期|196-210|共15页
  • 作者单位

    Beihang Univ State Key Lab Software Dev Environm Beijing Peoples R China;

    Singapore Management Univ Sch Informat Syst Singapore Singapore;

    Beihang Univ State Key Lab Software Dev Environm Beijing Peoples R China;

    Monash Univ Informat Technol Melbourne Vic Australia;

    Beihang Univ State Key Lab Software Dev Environm Beijing Peoples R China;

    Beihang Univ State Key Lab Software Dev Environm Beijing Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Integrator prediction; Code review; Open source; Github;

    机译:积分器预测;代码审查;开源;GitHub;

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