MetricHunter: A software metric dataset generator utilizing SourceMonitor upon public GitHub repositories

Yusuf Ozcevik, Osman Altay

SOFTWAREX(2023)

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摘要
Version control systems are pervasively consulted nowadays to obtain software metric datasets. Accordingly, machine learning is applied to predict different aspects of a software including quality monitoring, influence analysis, etc. However, construction of a metric dataset is challenging and the dataset content may affect the success of the learning-based models. In this study, we propose a dataset construction tool, MetricHunter, which is able to produce platform/language specific datasets that can be used for predicting the features of newly created software. The proposed tool is developed by C# programming language utilizing a known metric gathering tool, i.e. SourceMonitor, and the GitHub REST API for public repositories. Thus, one can construct a proper dataset from a graphical user interface by simply specifying the programming language or target platform. The outputs of the tool on a set of repositories are validated by investigating automatically generated attribute values and comparing them with the measurements of metric gathering tools as well as the GitHub metric values.& COPY; 2023 The Author(s). Published by Elsevier B.V.This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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关键词
Software quality,Software metrics,Dataset construction,Git version control system
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