Motives and Methods for Quantitative FLOSS Research

Motives and Methods for Quantitative FLOSS Research

Megan Conklin (Elon University, USA)
DOI: 10.4018/978-1-59140-999-1.ch022
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Abstract

This chapter explores the motivations and methods for mining (collecting, aggregating, distributing, and analyzing) data about free/libre open source software (FLOSS) projects. It first explores why there is a need for this type of data. Then the chapter outlines the current state-of-the art in collecting and using quantitative data about FLOSS project, focusing especially on the three main types of FLOSS data that have been gathered to date: data from large forges, data from small project sets, and survey data. Finally, the chapter will describe some possible areas for improvement and recommendations for the future of FLOSS data collection.

Key Terms in this Chapter

Data Mining: Collecting information in order to use that collected information for a specific purpose.

Quantitative Methods: Research based on the collection of numeric data.

Development Practices: Systems for creating a software product.

Free Software (FS): Software that others are open to use, copy, or modify.

Software Engineering: Creating/developing software products.

Open Source Software (OSS): Software designed in such a way that users can access/review the underlying operating code that allows that software to perform certain processes.

Data Analysis: Reviewing collected information to identify trends or patterns.

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