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Empirical Software Engineering

Erschienen in:

26.01.2018

Augmenting and structuring user queries to support efficient free-form code search

verfasst von: Raphael Sirres, Tegawendé F. Bissyandé, Dongsun Kim, David Lo, Jacques Klein, Kisub Kim, Yves Le Traon

Erschienen in: Empirical Software Engineering | Ausgabe 5/2018

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Abstract

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.

Vorheriger Artikel Revisiting the performance of automated approaches for the retrieval of duplicate reports in issue tracking systems that perform just-in-time duplicate retrieval

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https://github.com/about/press (verified 14.08.2015).

This is a real question asked by a user in this post: http://stackoverflow.com/questions/4951997/generating-random-words-in-javahttp://stackoverflow.com/questions/4951997/generating-random-words-in-java.

In this illustrative example, we excluded the actual post (http://stackoverflow.com/questions/4951997/generating-random-words-in-javahttp://stackoverflow.com/questions/4951997/generating-random-words-in-java) where this question is asked. To eliminate bias, in all experiments described in Section 5, in which we selected a question of a Q&A site as a subject, we removed the corresponding posts from the list of relevant posts to be used for augmenting the query.

https://goo.gl/MqETzP (last accessed 12.07.2015).

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We use the dump that contains the oldest data available since the launch of Stack Overflow in 2008.

https://api.stackexchange.com/

Lucene’s (version 4) English default stop word set.

http://lucene.apache.org

Ohloh is now OpenHub.

Despite different queries, our query sets are similar to those of Lv et al. (2015) and representatives of common developer search queries.

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Titel: Augmenting and structuring user queries to support efficient free-form code search
verfasst von: Raphael Sirres
Tegawendé F. Bissyandé
Dongsun Kim
David Lo
Jacques Klein
Kisub Kim
Yves Le Traon
Publikationsdatum: 26.01.2018
Verlag: Springer US
Erschienen in: Empirical Software Engineering / Ausgabe 5/2018
Print ISSN: 1382-3256
Elektronische ISSN: 1573-7616
DOI: https://doi.org/10.1007/s10664-017-9544-y

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