Applying Epistemic Network Analysis to Open Source Software Projects

The massive emergence of Open Source Software (OSS) projects led to the rapid increment of data available to software engineers and those who would like to contribute to an OSS project. There is an arising need for a way to analyze and draw conclusions about the value of an OSS project, from an epistemic point of view. OSS projects have been used for a long time as vehicles for learning programming and software engineering. However, there is a need for more evidence about the scientific value conveyed by OSS projects. We posit that if we deeply study the dialogues of software engineers involved in the communities of the various projects and draw conclusions from them, this can be an additional way of assessing OSS projects. Learning analytics, data mining and data science provide diverse statistical and computational approaches to analyzing data. In this work, we describe Epistemic Network Analysis (ENA), a network analysis technique used by a growing community of researchers to support thick descriptions based on large volumes of data. ENA is based on the theory of epistemic frames. The theory of epistemic frames models the ways of being, thinking and acting inside some community of practice. In this research, we focus on the epistemic frame of software engineering and discuss the elements of this frame: the knowledge, the set of skills and values and the set of processes for making and justifying decisions. We coded the discourses of two well-known open source projects, LibreOffice and OpenOffice, and we used the online tool ENA WebKit to analyze the coded rows of the discourses, but also to visualize and compare the networks of different units of data. We conducted three types of experiments and comparisons on the mean networks of the two projects, on the networks of the different bugs, as well as on the networks of some software engineers who participated in the discussions, and we came to conclusions about how epistemic these dialogues were and therefore assessing their educational value. This is an introductory work utilizing the ENA method for OSS discourse analysis. We believe that the rational presented in this paper can lead to a set of processes on evaluating OSS projects based on their epistemology and at the same time, become an educational tool for software engineering courses and research groups.

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Journal
International Journal of Software Engineering and Knowledge Engineering
Published
2024-12-31
DOI
https://doi.org/10.1142/s0218194025500093
Primary Topic
Machine Learning in Materials Science
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article
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article

Applying Epistemic Network Analysis to Open Source Software Projects

Ioannis G. Stamelos, Κωνσταντίνα Παπαδοπούλου, Apostolos Kritikos
International Journal of Software Engineering and Knowledge Engineering
Machine Learning in Materials Science
article

Applying Epistemic Network Analysis to Open Source Software Projects

Ioannis G. Stamelos, Κωνσταντίνα Παπαδοπούλου, Apostolos Kritikos
article en

Abstract

The massive emergence of Open Source Software (OSS) projects led to the rapid increment of data available to software engineers and those who would like to contribute to an OSS project. There is an arising need for a way to analyze and draw conclusions about the value of an OSS project, from an epistemic point of view. OSS projects have been used for a long time as vehicles for learning programming and software engineering. However, there is a need for more evidence about the scientific value conveyed by OSS projects. We posit that if we deeply study the dialogues of software engineers involved in the communities of the various projects and draw conclusions from them, this can be an additional way of assessing OSS projects. Learning analytics, data mining and data science provide diverse statistical and computational approaches to analyzing data. In this work, we describe Epistemic Network Analysis (ENA), a network analysis technique used by a growing community of researchers to support thick descriptions based on large volumes of data. ENA is based on the theory of epistemic frames. The theory of epistemic frames models the ways of being, thinking and acting inside some community of practice. In this research, we focus on the epistemic frame of software engineering and discuss the elements of this frame: the knowledge, the set of skills and values and the set of processes for making and justifying decisions. We coded the discourses of two well-known open source projects, LibreOffice and OpenOffice, and we used the online tool ENA WebKit to analyze the coded rows of the discourses, but also to visualize and compare the networks of different units of data. We conducted three types of experiments and comparisons on the mean networks of the two projects, on the networks of the different bugs, as well as on the networks of some software engineers who participated in the discussions, and we came to conclusions about how epistemic these dialogues were and therefore assessing their educational value. This is an introductory work utilizing the ENA method for OSS discourse analysis. We believe that the rational presented in this paper can lead to a set of processes on evaluating OSS projects based on their epistemology and at the same time, become an educational tool for software engineering courses and research groups.

International Journal of Software Engineering and Knowledge EngineeringVol. 35(04)
Aristotle University of Thessaloniki (GR)
Partnerships for the goals
Openalex Percentile: Top 84%
Machine Learning in Materials Science
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