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Progress in Artificial Intelligence

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28.03.2018 | Regular Paper

Emerging topics in mining software repositories

Machine learning in software repositories and datasets

verfasst von: Diego Güemes-Peña, Carlos López-Nozal, Raúl Marticorena-Sánchez, Jesús Maudes-Raedo

Erschienen in: Progress in Artificial Intelligence | Ausgabe 3/2018

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Abstract

A software process is a set of related activities that culminates in the production of a software package: specification, design, implementation, testing, evolution into new versions, and maintenance. There are also other supporting activities such as configuration and change management, quality assurance, project management, evaluation of user experience, etc. Software repositories are infrastructures to support all these activities. They can be composed with several systems that include code change management, bug tracking, code review, build system, release binaries, wikis, forums, etc. This position paper on mining software repositories presents a review and a discussion of research in this field over the past decade. We also identify applied machine learning strategies, current working topics, and future challenges for the improvement of company decision-making systems. Machine learning is defined as the process of discovering patterns in data. It can be applied to software repositories, since every change is recorded as data. Companies can then use these patterns as the basis for their decision-making systems and for knowledge discovery.

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Titel: Emerging topics in mining software repositories
Machine learning in software repositories and datasets
verfasst von: Diego Güemes-Peña
Carlos López-Nozal
Raúl Marticorena-Sánchez
Jesús Maudes-Raedo
Publikationsdatum: 28.03.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Progress in Artificial Intelligence / Ausgabe 3/2018
Print ISSN: 2192-6352
Elektronische ISSN: 2192-6360
DOI: https://doi.org/10.1007/s13748-018-0147-7

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