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GitHub Crawler is an application that has been developed within the context of the SDK4ED project, as part of the Dependability Toolbox, in order to enable the automatic collection and static analysis of a large number of open-source software repositories from GitHub.
The GitHub Crawler is responsible for (i) downloading a large number of open-source repositories from GitHub based on a user's query, (ii) compiling the downloaded repositories, and (iii) analyzing the downloaded repositories with CKJM Extended (link) and CCCC (link) static code analyzers, in order to compute popular software metrics. GitHub crawler is useful for researchers and practicionairs that would like to generate benchmark repositories of open-source software applications for further analysis and processing, which are particularly important for the conduction of empirical studies. Currently, the GitHub Crawler can download applications written in any programming language; however, it can compute software metrics only for software repositories written in Java, C, and C++.
The GitHub Crawler is responsible for (i) downloading a large number of open-source repositories from GitHub based on a user's query, (ii) compiling the downloaded repositories, and (iii) analyzing the downloaded repositories with CKJM Extended (link) and CCCC (link) static code analyzers, in order to compute popular software metrics. GitHub crawler is useful for researchers and <span dir="">practitioners</span> that would like to generate benchmark repositories of open-source software applications for further analysis and processing, which are particularly important for the conduction of empirical studies. Currently, the GitHub Crawler can download applications written in any programming language; however, it can compute software metrics only for software repositories written in Java, C, and C++.
The GitHub Crawler was utilized by the SDK4ED project for (i) constructing the Benchmark Repository that was utilized for calibrating the Software Security Assessment Model (SAM) (link) and (ii) for constructing software metrics-based Vulnerability Prediction Models (VPMs) (link) that are part of the Dependability Toolbox (link). It is also utilized by the Dependability Toolbox for constructing security benchmarks.
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