Augmenting and structuring user queries to support efficient free-form code search
Source code terms such as method names and variable types are often different from conceptual words mentioned in a search query. This vocabulary mismatch problem can make code search inefficient. In this paper, we present COde voCABUlary (CoCaBu), an approach to resolving the vocabulary mismatch pro...
Saved in:
Main Authors: | , , , , , , |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2018
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/4129 https://ink.library.smu.edu.sg/context/sis_research/article/5132/viewcontent/Augmenting_and_structuring_user_queries_to_support.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
id |
sg-smu-ink.sis_research-5132 |
---|---|
record_format |
dspace |
spelling |
sg-smu-ink.sis_research-51322020-01-20T03:26:42Z Augmenting and structuring user queries to support efficient free-form code search SIRRES, Raphael BISSYANDE, Tegawendé F. KIM, Dongsun LO, David KLEIN, Jacques KIM, Kisub TRAON, Yves Le Source code terms such as method names and variable types are often different from conceptual words mentioned in a search query. This vocabulary mismatch problem can make code search inefficient. In this paper, we present COde voCABUlary (CoCaBu), an approach to resolving the vocabulary mismatch problem when dealing with free-form code search queries. Our approach leverages common developer questions and the associated expert answers to augment user queries with the relevant, but missing, structural code entities in order to improve the performance of matching relevant code examples within large code repositories. To instantiate this approach, we build GitSearch, a code search engine, on top of GitHub and Stack Overflow Q&A data. We evaluate GitSearch in several dimensions to demonstrate that (1) its code search results are correct with respect to user-accepted answers; (2) the results are qualitatively better than those of existing Internet-scale code search engines; (3) our engine is competitive against web search engines, such as Google, in helping users solve programming tasks; and (4) GitSearch provides code examples that are acceptable or interesting to the community as answers for Stack Overflow questions. 2018-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4129 info:doi/10.1007/s10664-017-9544-y https://ink.library.smu.edu.sg/context/sis_research/article/5132/viewcontent/Augmenting_and_structuring_user_queries_to_support.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 Code search GitHub Free-form search Query augmentation StackOverflow Vocabulary mismatch Computer Engineering Programming Languages and Compilers Software Engineering |
institution |
Singapore Management University |
building |
SMU Libraries |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
SMU Libraries |
collection |
InK@SMU |
language |
English |
topic |
Code search GitHub Free-form search Query augmentation StackOverflow Vocabulary mismatch Computer Engineering Programming Languages and Compilers Software Engineering |
spellingShingle |
Code search GitHub Free-form search Query augmentation StackOverflow Vocabulary mismatch Computer Engineering Programming Languages and Compilers Software Engineering SIRRES, Raphael BISSYANDE, Tegawendé F. KIM, Dongsun LO, David KLEIN, Jacques KIM, Kisub TRAON, Yves Le Augmenting and structuring user queries to support efficient free-form code search |
description |
Source code terms such as method names and variable types are often different from conceptual words mentioned in a search query. This vocabulary mismatch problem can make code search inefficient. In this paper, we present COde voCABUlary (CoCaBu), an approach to resolving the vocabulary mismatch problem when dealing with free-form code search queries. Our approach leverages common developer questions and the associated expert answers to augment user queries with the relevant, but missing, structural code entities in order to improve the performance of matching relevant code examples within large code repositories. To instantiate this approach, we build GitSearch, a code search engine, on top of GitHub and Stack Overflow Q&A data. We evaluate GitSearch in several dimensions to demonstrate that (1) its code search results are correct with respect to user-accepted answers; (2) the results are qualitatively better than those of existing Internet-scale code search engines; (3) our engine is competitive against web search engines, such as Google, in helping users solve programming tasks; and (4) GitSearch provides code examples that are acceptable or interesting to the community as answers for Stack Overflow questions. |
format |
text |
author |
SIRRES, Raphael BISSYANDE, Tegawendé F. KIM, Dongsun LO, David KLEIN, Jacques KIM, Kisub TRAON, Yves Le |
author_facet |
SIRRES, Raphael BISSYANDE, Tegawendé F. KIM, Dongsun LO, David KLEIN, Jacques KIM, Kisub TRAON, Yves Le |
author_sort |
SIRRES, Raphael |
title |
Augmenting and structuring user queries to support efficient free-form code search |
title_short |
Augmenting and structuring user queries to support efficient free-form code search |
title_full |
Augmenting and structuring user queries to support efficient free-form code search |
title_fullStr |
Augmenting and structuring user queries to support efficient free-form code search |
title_full_unstemmed |
Augmenting and structuring user queries to support efficient free-form code search |
title_sort |
augmenting and structuring user queries to support efficient free-form code search |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2018 |
url |
https://ink.library.smu.edu.sg/sis_research/4129 https://ink.library.smu.edu.sg/context/sis_research/article/5132/viewcontent/Augmenting_and_structuring_user_queries_to_support.pdf |
_version_ |
1770574345321578496 |