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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-12-01
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| Series: | Data in Brief |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340919310674 |
| _version_ | 1818583917049937920 |
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| author | Ben Gelman Banjo Obayomi Jessica Moore David Slater |
| author_facet | Ben Gelman Banjo Obayomi Jessica Moore David Slater |
| author_sort | Ben Gelman |
| collection | DOAJ |
| 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. Keywords: Source code, Code comments, Bug detection, Static analysis |
| first_indexed | 2024-12-16T08:12:53Z |
| format | Article |
| id | doaj.art-44847eea75f948ffa9b130c94ee0490e |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-12-16T08:12:53Z |
| publishDate | 2019-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-44847eea75f948ffa9b130c94ee0490e2022-12-21T22:38:19ZengElsevierData in Brief2352-34092019-12-0127Source code analysis datasetBen Gelman0Banjo Obayomi1Jessica Moore2David Slater3Machine Learning Group, Two Six Labs, 901 N. Stuart St, Suite 1000, Arlington, VA, 22203, USAMachine Learning Group, Two Six Labs, 901 N. Stuart St, Suite 1000, Arlington, VA, 22203, USAMachine Learning Group, Two Six Labs, 901 N. Stuart St, Suite 1000, Arlington, VA, 22203, USACorresponding author.; Machine Learning Group, Two Six Labs, 901 N. Stuart St, Suite 1000, Arlington, VA, 22203, USAThe 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. Keywords: Source code, Code comments, Bug detection, Static analysishttp://www.sciencedirect.com/science/article/pii/S2352340919310674 |
| spellingShingle | Ben Gelman Banjo Obayomi Jessica Moore David Slater Source code analysis dataset Data in Brief |
| 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 |
| url | http://www.sciencedirect.com/science/article/pii/S2352340919310674 |
| work_keys_str_mv | AT bengelman sourcecodeanalysisdataset AT banjoobayomi sourcecodeanalysisdataset AT jessicamoore sourcecodeanalysisdataset AT davidslater sourcecodeanalysisdataset |