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CVExplorer: identifying candidate developers by mining and exploring their open source contributions.

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dc.contributor.author Greene, GJ
dc.contributor.author Fischer, B
dc.date.accessioned 2017-01-16T09:48:23Z
dc.date.available 2017-01-16T09:48:23Z
dc.date.issued 2016-09
dc.identifier.citation Greene, G.J. and Fischer, B. 2016. CVExplorer: identifying candidate developers by mining and exploring their open source contributions. In:31st IEEE/ACM International Conference on Automated Software Engineering (ASE), 3-7 September 2016, Singapore, Singapore. en_US
dc.identifier.uri http://dl.acm.org/citation.cfm?id=2970285
dc.identifier.uri http://dl.acm.org/citation.cfm?doid=2970276.2970285
dc.identifier.uri http://hdl.handle.net/10204/8906
dc.description 31st IEEE/ACM International Conference on Automated Software Engineering (ASE), 3-7 September 2016, Singapore, Singapore.Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. en_US
dc.description.abstract Open source code contributions contain a large amount of technical skill information about developers, which can help to identify suitable candidates for a particular development job and therefore impact the success of a development team. We develop CVExplorer as a tool to extract, visualize, and explore relevant technical skills data from GitHub, such as languages and libraries used. It allows non-technical users to filter and identify developers according to technical skills demonstrated across all of their open source contributions, in order to support more accurate candidate identification. We demonstrate the usefulness of CVExplorer by using it to recommend candidates for open positions in two companies. en_US
dc.language.iso en en_US
dc.publisher Association for Computing Machinery (ACM) en_US
dc.relation.ispartofseries Workflow;17611
dc.subject Identifying candidate developers en_US
dc.subject Developer skills identification en_US
dc.subject Mining software repositories en_US
dc.title CVExplorer: identifying candidate developers by mining and exploring their open source contributions. en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Greene, G., & Fischer, B. (2016). CVExplorer: identifying candidate developers by mining and exploring their open source contributions. Association for Computing Machinery (ACM). http://hdl.handle.net/10204/8906 en_ZA
dc.identifier.chicagocitation Greene, GJ, and B Fischer. "CVExplorer: identifying candidate developers by mining and exploring their open source contributions." (2016): http://hdl.handle.net/10204/8906 en_ZA
dc.identifier.vancouvercitation Greene G, Fischer B, CVExplorer: identifying candidate developers by mining and exploring their open source contributions; Association for Computing Machinery (ACM); 2016. http://hdl.handle.net/10204/8906 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Greene, GJ AU - Fischer, B AB - Open source code contributions contain a large amount of technical skill information about developers, which can help to identify suitable candidates for a particular development job and therefore impact the success of a development team. We develop CVExplorer as a tool to extract, visualize, and explore relevant technical skills data from GitHub, such as languages and libraries used. It allows non-technical users to filter and identify developers according to technical skills demonstrated across all of their open source contributions, in order to support more accurate candidate identification. We demonstrate the usefulness of CVExplorer by using it to recommend candidates for open positions in two companies. DA - 2016-09 DB - ResearchSpace DP - CSIR KW - Identifying candidate developers KW - Developer skills identification KW - Mining software repositories LK - https://researchspace.csir.co.za PY - 2016 T1 - CVExplorer: identifying candidate developers by mining and exploring their open source contributions TI - CVExplorer: identifying candidate developers by mining and exploring their open source contributions UR - http://hdl.handle.net/10204/8906 ER - en_ZA


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