RACK: Code Search in the IDE Using Crowdsourced Knowledge
Traditional code search engines often do not perform well with natural language queries since they mostly apply keyword matching. These engines thus require carefully designed queries containing information about programming APIs for code search. Unfortunately, existing studies suggest that preparin...
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sg-smu-ink.sis_research-47002017-11-15T02:48:30Z RACK: Code Search in the IDE Using Crowdsourced Knowledge RAHMAN, Mohammad Masudur ROY, Chanchal K. LO, David Traditional code search engines often do not perform well with natural language queries since they mostly apply keyword matching. These engines thus require carefully designed queries containing information about programming APIs for code search. Unfortunately, existing studies suggest that preparing an effective query for code search is both challenging and time consuming for the developers. In this paper, we propose a novel code search tool-RACK-that returns relevant source code for a given code search query written in natural language text. The tool first translates the query into a list of relevant API classes by mining keyword-API associations from the crowdsourced knowledge of Stack Overflow, and then applies the reformulated query to GitHub code search API for collecting relevant results. Once a query related to a programming task is submitted, the tool automatically mines relevant code snippets from thousands of open-source projects, and displays them as a ranked list within the context of the developer's programming environment-the IDE. Tool page: http://www.usask.ca/~masud.rahman/rack. 2017-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3698 info:doi/10.1109/ICSE-C.2017.11 https://ink.library.smu.edu.sg/context/sis_research/article/4700/viewcontent/1589a051.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Tools Natural languages Programming Search engines Context Search problems Vocabulary Programming Languages and Compilers Software Engineering |
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Tools Natural languages Programming Search engines Context Search problems Vocabulary Programming Languages and Compilers Software Engineering RAHMAN, Mohammad Masudur ROY, Chanchal K. LO, David RACK: Code Search in the IDE Using Crowdsourced Knowledge |
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Traditional code search engines often do not perform well with natural language queries since they mostly apply keyword matching. These engines thus require carefully designed queries containing information about programming APIs for code search. Unfortunately, existing studies suggest that preparing an effective query for code search is both challenging and time consuming for the developers. In this paper, we propose a novel code search tool-RACK-that returns relevant source code for a given code search query written in natural language text. The tool first translates the query into a list of relevant API classes by mining keyword-API associations from the crowdsourced knowledge of Stack Overflow, and then applies the reformulated query to GitHub code search API for collecting relevant results. Once a query related to a programming task is submitted, the tool automatically mines relevant code snippets from thousands of open-source projects, and displays them as a ranked list within the context of the developer's programming environment-the IDE. Tool page: http://www.usask.ca/~masud.rahman/rack. |
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RAHMAN, Mohammad Masudur ROY, Chanchal K. LO, David |
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RAHMAN, Mohammad Masudur ROY, Chanchal K. LO, David |
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RAHMAN, Mohammad Masudur |
title |
RACK: Code Search in the IDE Using Crowdsourced Knowledge |
title_short |
RACK: Code Search in the IDE Using Crowdsourced Knowledge |
title_full |
RACK: Code Search in the IDE Using Crowdsourced Knowledge |
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RACK: Code Search in the IDE Using Crowdsourced Knowledge |
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RACK: Code Search in the IDE Using Crowdsourced Knowledge |
title_sort |
rack: code search in the ide using crowdsourced knowledge |
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Institutional Knowledge at Singapore Management University |
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2017 |
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https://ink.library.smu.edu.sg/sis_research/3698 https://ink.library.smu.edu.sg/context/sis_research/article/4700/viewcontent/1589a051.pdf |
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