Tools and Datasets for Mining Libre Software Repositories

Tools and Datasets for Mining Libre Software Repositories

Gregorio Robles (Universidad Rey Juan Carlos, Spain), Jesús M. González-Barahona (Universidad Rey Juan Carlos, Spain), Daniel Izquierdo-Cortazar (Universidad Rey Juan Carlos, Spain) and Israel Herraiz (Universidad Alfonso X el Sabi, Spain)
DOI: 10.4018/978-1-61350-456-7.ch305
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Abstract

Thanks to the open nature of libre (free, open source) software projects, researchers have gained access to a rich set of data related to various aspects of software development. Although it is usually publicly available on the Internet, obtaining and analyzing the data in a convenient way is not an easy task, and many considerations have to be taken into account. In this chapter we introduce the most relevant data sources that can be found in libre software projects and that are commonly studied by scholars: source code releases, source code management systems, mailing lists and issue (bug) tracking systems. The chapter also provides some advice on the problems that can be found when retrieving and preparing the data sources for a later analysis, as well as information about the tools and datasets that support these tasks.
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2. First Steps Before The Analysis

There are some steps to be walked before the analysis of data from libre software projects can be started. First of all, the relevant data sources have to be identified. After that, the data has to be retrieved from the corresponding data repositories. Only then, the researcher can really start to analyze the data.

It is important to notice that there may be several ways of accessing the same kind of data, depending on the project and how it handles it. There are several different tools and systems that projects use, and they also have different usage conventions. For instance, the use of tags, comments, among others, may differ from one project to another, and can be of paramount importance to tell bugs appart from new feature requests in a BTS. The complexity and feasibility of both identification and retrieval depend, therefore, of the project. Figure 1 shows a diagram with all the steps that have to be accomplished for any source considered in the studies.

Figure 1.

Whole process: from identification of the data sources to analysis of the data

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