Tie Strength Metrics to Rank Pairs of Developers from GitHub

J. Inf. Data Manag. Pub Date : 2018-06-20 DOI:10.5753/jidm.2018.1637

Natércia A. Batista, Guilherme A. de Sousa, Michele A. Brandão, Ana Paula Couto da Silva, Mirella M. Moro

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引用次数: 5

Abstract

The Web provides huge volumes of data, which makes efficient data collecting and processing not easy tasks. An example of such volumes is in software repositories, a type of Web storage platform for software and projects,their developers and companies. In this work, we first present a systematic literature review over topics related to such repositories. Then, we extract their data and enrich it by building a development network. Based on such a network, we investigate tie strength metrics on their capability of defining new information through a correlation analysis. We also use the metrics to rank pairs of developers by considering three different aggregate methods. Our experimental analysis shows different results for each ranking method when considering all pairs of developers, which reveals the difficulty of choosing the best way to rank pairs of developers. However, when considering the top 10 best ranked pairs, two methods present similar results. Also, the combination of tie strength metrics with ranking aggregated methods allows to identify important developers in the network and their collaboration strength.

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将强度指标与GitHub的开发人员配对

Web提供了大量的数据，这使得有效的数据收集和处理变得不容易。此类卷的一个例子是软件存储库，这是一种用于软件和项目、开发人员和公司的Web存储平台。在这项工作中，我们首先对与此类存储库相关的主题进行了系统的文献综述。然后，我们提取他们的数据，并通过建立一个开发网络来丰富它。基于这样的网络，我们通过相关分析研究了它们定义新信息的能力。我们还通过考虑三种不同的聚合方法，使用指标对开发人员进行排名。我们的实验分析显示，当考虑到所有成对的开发者时，每种排名方法的结果不同，这揭示了选择最佳方法对开发者进行排名的难度。然而，当考虑排名前十的组合时，两种方法给出了相似的结果。此外，将联系强度指标与排名聚合方法相结合，可以识别网络中重要的开发人员及其协作强度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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J. Inf. Data Manag.

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