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Source code analysis dataset

The data in this article pair source code with three artifacts from 108,568 projects downloaded from Github that have a redistributable license and at least 10 stars. The first set of pairs connects snippets of source code in C, C++, Java, and Python with their corresponding comments, which are extr...

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Detalles Bibliográficos
Autores principales: Gelman, Ben, Obayomi, Banjo, Moore, Jessica, Slater, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6859235/
https://www.ncbi.nlm.nih.gov/pubmed/31763386
http://dx.doi.org/10.1016/j.dib.2019.104712
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author Gelman, Ben
Obayomi, Banjo
Moore, Jessica
Slater, David
author_facet Gelman, Ben
Obayomi, Banjo
Moore, Jessica
Slater, David
author_sort Gelman, Ben
collection PubMed
description The data in this article pair source code with three artifacts from 108,568 projects downloaded from Github that have a redistributable license and at least 10 stars. The first set of pairs connects snippets of source code in C, C++, Java, and Python with their corresponding comments, which are extracted using Doxygen. The second set of pairs connects raw C and C++ source code repositories with the build artifacts of that code, which are obtained by running the make command. The last set of pairs connects raw C and C++ source code repositories with potential code vulnerabilities, which are determined by running the Infer static analyzer. The code and comment pairs can be used for tasks such as predicting comments or creating natural language descriptions of code. The code and build artifact pairs can be used for tasks such as reverse engineering or improving intermediate representations of code from decompiled binaries. The code and static analyzer pairs can be used for tasks such as machine learning approaches to vulnerability discovery.
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spelling pubmed-68592352019-11-22 Source code analysis dataset Gelman, Ben Obayomi, Banjo Moore, Jessica Slater, David Data Brief Computer Science The data in this article pair source code with three artifacts from 108,568 projects downloaded from Github that have a redistributable license and at least 10 stars. The first set of pairs connects snippets of source code in C, C++, Java, and Python with their corresponding comments, which are extracted using Doxygen. The second set of pairs connects raw C and C++ source code repositories with the build artifacts of that code, which are obtained by running the make command. The last set of pairs connects raw C and C++ source code repositories with potential code vulnerabilities, which are determined by running the Infer static analyzer. The code and comment pairs can be used for tasks such as predicting comments or creating natural language descriptions of code. The code and build artifact pairs can be used for tasks such as reverse engineering or improving intermediate representations of code from decompiled binaries. The code and static analyzer pairs can be used for tasks such as machine learning approaches to vulnerability discovery. Elsevier 2019-10-24 /pmc/articles/PMC6859235/ /pubmed/31763386 http://dx.doi.org/10.1016/j.dib.2019.104712 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Computer Science
Gelman, Ben
Obayomi, Banjo
Moore, Jessica
Slater, David
Source code analysis dataset
title Source code analysis dataset
title_full Source code analysis dataset
title_fullStr Source code analysis dataset
title_full_unstemmed Source code analysis dataset
title_short Source code analysis dataset
title_sort source code analysis dataset
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6859235/
https://www.ncbi.nlm.nih.gov/pubmed/31763386
http://dx.doi.org/10.1016/j.dib.2019.104712
work_keys_str_mv AT gelmanben sourcecodeanalysisdataset
AT obayomibanjo sourcecodeanalysisdataset
AT moorejessica sourcecodeanalysisdataset
AT slaterdavid sourcecodeanalysisdataset