Using an information retrieval system to retrieve source code samples

Sindhgatta, Renuka

doi:10.1145/1134285.1134448

Cited by 49 publications

(36 citation statements)

References 7 publications

(5 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Modern CASE tools are bringing sophisticated search capabilities into the IDE, extending traditionally limited browsing and searching capabilities [18][19][20][21][22][23]. These tools vary in terms of the provided features, but some common ideas that are prevalent among them are the use of the developer's current context to generate queries and the integration of ranking techniques for the search results.…”

Section: Related Workmentioning

confidence: 99%

Using Thesaurus-Based Tag Clouds to Improve Test-Driven Code Search

Lemos

Paula

Konishi

et al. 2013

2013 VII Brazilian Symposium on Software Components, Architectures and Reuse

View full text Add to dashboard Cite

Test-driven code search (TDCS) is an approach to code search and reuse that uses test cases as inputs to form the search query. Together with the test cases that provide more semantics to the search task, keywords taken from class and method names are still required. Therefore, the effectiveness of the approach also relies on how good these keywords are, i.e., how frequently they are chosen by developers to name the desired functions. To help users choose adequate words in their query test cases, visual aids can be used. In this paper we propose thesaurus-based tag clouds to show developers terms that are more frequently used in the code repository to improve their search. Terms are generated by looking up words similar to the initial keywords on a thesaurus. Tag clouds are then formed based on the frequency in which these terms appear in the code base. Our approach was implemented with an English thesaurus as an extension to CodeGenie, a Java-and Eclipse-based TDCS tool. Our evaluation shows that the approach can help improve the number of returned results. We also noticed the visual aid can be especially useful for non-native speakers of the language in which the code repository is written. These users are frequently unaware of the most common terms used to name specific functionality in the code, in the given language.

show abstract

Section: Related Workmentioning

confidence: 99%

Using Thesaurus-Based Tag Clouds to Improve Test-Driven Code Search

Lemos

Paula

Konishi

et al. 2013

2013 VII Brazilian Symposium on Software Components, Architectures and Reuse

View full text Add to dashboard Cite

show abstract

“…Modern software engineering tools are bringing more sophisticated search capabilities into the development environment extending the traditionally limited browsing and searching capabilities [19,30,44,39,42]. These tools vary in terms of the features they provide but some common ideas that are prevalent among them are the use of the developer's current context to generate queries and the integration of ranking techniques for the search results.…”

Section: Related Workmentioning

confidence: 99%

A test-driven approach to code search and its application to the reuse of auxiliary functionality

Lemos

Bajracharya

Ossher

et al. 2011

Information and Software Technology

View full text Add to dashboard Cite

a b s t r a c tContext: Software developers spend considerable effort implementing auxiliary functionality used by the main features of a system (e.g., compressing/decompressing files, encryption/decription of data, scaling/ rotating images). With the increasing amount of open source code available on the Internet, time and effort can be saved by reusing these utilities through informal practices of code search and reuse. However, when this type of reuse is performed in an ad hoc manner, it can be tedious and error-prone: code results have to be manually inspected and integrated into the workspace. Objective: In this paper we introduce and evaluate the use of test cases as an interface for automating code search and reuse. We call our approach Test-Driven Code Search (TDCS). Test cases serve two purposes: (1) they define the behavior of the desired functionality to be searched; and (2) they test the matching results for suitability in the local context. We also describe CodeGenie, an Eclipse plugin we have developed that performs TDCS using a code search engine called Sourcerer. Method: Our evaluation consists of two studies: an applicability study with 34 different features that were searched using CodeGenie; and a performance study comparing CodeGenie, Google Code Search, and a manual approach. Results: Both studies present evidence of the applicability and good performance of TDCS in the reuse of auxiliary functionality. Conclusion: This paper presents an approach to source code search and its application to the reuse of auxiliary functionality. Our exploratory evaluation shows promising results, which motivates the use and further investigation of TDCS.

show abstract

“…Google general-purpose search engine appears to treat code as pure text, as it does for Web pages. Likewise, other tools such as JSearch (Sindhgatta 2006) and JIRiss (Poshyvanyk et al 2006) employ standard IR techniques, but without the benefit of graph-based approaches. An over-arching goal in the design of Sourcerer is to allow for the combination of text and graph-based heuristics to improve the efficiency with which code is searched and retrieved.…”

Section: Improving Code Searchmentioning

confidence: 99%

“…JSearch (Sindhgatta 2006) and JIRiss (Poshyvanyk et al 2006) are two other tools that employ IR techniques to code search. JSearch indexes source code using Lucene after extracting interesting syntactic entities whereas JIRiss uses Latent Semantic Indexing (Marcus et al 2004).…”

Section: Search Enginesmentioning

confidence: 99%

Sourcerer: mining and searching internet-scale software repositories

Linstead

Bajracharya

Ngo

et al. 2008

Data Min Knowl Disc

215

111

View full text Add to dashboard Cite

Large repositories of source code available over the Internet, or within large organizations, create new challenges and opportunities for data mining and statistical machine learning. Here we first develop Sourcerer, an infrastructure for the automated crawling, parsing, fingerprinting, and database storage of open source software on an Internet-scale. In one experiment, we gather 4,632 Java projects from SourceForge and Apache totaling over 38 million lines of code from 9,250 developers. Simple statistical analyses of the data first reveal robust power-law behavior for package, method call, and lexical containment distributions. We then develop and apply unsupervised, probabilistic, topic and author-topic (AT) models to automatically 123 Mining and searching internet-scale software repositories 301 discover the topics embedded in the code and extract topic-word, document-topic, and AT distributions. In addition to serving as a convenient summary for program function and developer activities, these and other related distributions provide a statistical and information-theoretic basis for quantifying and analyzing source file similarity, developer similarity and competence, topic scattering, and document tangling, with direct applications to software engineering an software development staffing. Finally, by combining software textual content with structural information captured by our CodeRank approach, we are able to significantly improve software retrieval performance, increasing the area under the curve (AUC) retrieval metric to 0.92-roughly 10-30% better than previous approaches based on text alone. A prototype of the system is available at: http://sourcerer.ics.uci.edu.

show abstract

Using an information retrieval system to retrieve source code samples

Cited by 49 publications

References 7 publications

Using Thesaurus-Based Tag Clouds to Improve Test-Driven Code Search

Using Thesaurus-Based Tag Clouds to Improve Test-Driven Code Search

A test-driven approach to code search and its application to the reuse of auxiliary functionality

Sourcerer: mining and searching internet-scale software repositories

Contact Info

Product

Resources

About