A Comparison of Three Algorithms for Computing Truck Factors
A Comparison of Three Algorithms for Computing Truck Factors
复制标题
三种卡车系数计算算法的比较
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
K. Ferreira
中科院分区：
文献类型：
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作者：
Mívian M. Ferreira;M. T. Valente;K. Ferreira
卡车因素（也称为巴士因素或彩票号码）是在项目丧失能力之前必须被卡车撞击（或离开）的最小开发人员数量。因此，它是一种揭示项目中知识集中度和关键开发人员的度量。由于这些信息对项目经理的重要性，提出了使用从版本控制系统中提取的维护活动数据来自动计算卡车因子的算法。然而，据我们所知，我们仍然缺乏比较这些算法产生的结果准确性的研究。因此，在本文中，我们评估和比较了三种卡车因子算法的结果。为此，我们通过咨询开源系统的开发人员来确定35个开源系统的卡车因素。结果表明，两种算法都非常准确，特别是当系统具有较小的卡车因子时。我们还评估了不同阈值和配置对算法结果的影响。
Truck Factor (also known as Bus Factor or Lottery Number) is the minimal number of developers that have to be hit by a truck (or leave) before a project is incapacitated. Therefore, it is a measure that reveals the concentration of knowledge and the key developers in a project. Due to the importance of this information to project managers, algorithms were proposed to automatically compute Truck Factors, using maintenance activity data extracted from version control systems. However, to the best of our knowledge, we still lack studies that compare the accuracy of the results produced by such algorithms. Therefore, in this paper, we evaluate and compare the results of three Truck Factor algorithms. To this end, we empirically determine the truck factors of 35 open-source systems by consulting their developers. Our results show that two algorithms are very accurate, especially when the systems have a small Truck Factor. We also evaluate the impact of different thresholds and configurations in algorithm results.