Communication Dans Un Congrès Année : 2025

Automatic Classification of Software Repositories: a Systematic Mapping Study

Résumé

The rapid growth of software repositories on development platforms such as GitHub, as well as archives like Software Heritage, prompts the need for better repository classification. Machine learning is increasingly used to automate this classification, but there are no secondary studies analyzing this research landscape. We present a systematic mapping study of 43 primary sources published between 2002 and 2023, where we examine the goals, inputs, outputs, training, and evaluation processes involved in automatic repository classification. Our findings reveal a growing interest in automatic classification, particularly to enhance the discoverability and recommendation of relevant repositories. Other applications, such as classification for mining studies, were surprisingly underrepresented. We also observe that a lack of standardized datasets, classification tasks, and evaluation metrics makes it difficult to compare the performance of different techniques.

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Est complété par 10.5281/zenodo.14773537 Jeu de données anonymous. (2025). Automatic Classification of Software Repositories: A Systematic Mapping Study - replication package [Data set]. Zenodo. https://doi.org/10.5281/ZENODO.14773537

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hal-05049757 , version 1 (28-04-2025)

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  • HAL Id : hal-05049757 , version 1

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Stefano Balla, Thomas Degueule, Romain Robbes, Jean-Rémy Falleri, Stefano Zacchiroli. Automatic Classification of Software Repositories: a Systematic Mapping Study. International Conference on Evaluation and Assessment in Software Engineering (EASE 2025), Jun 2025, Istanbul, Turkey. ⟨hal-05049757⟩
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