NDLI: Leveraging usage similarity for effective retrieval of examples in code repositories

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Leveraging usage similarity for effective retrieval of examples in code repositories

Content Provider	ACM Digital Library
Author	Ossher, Joel Lopes, Cristina V. Bajracharya, Sushil K.
Abstract	Developers often learn to use APIs (Application Programming Interfaces) by looking at existing examples of API usage. Code repositories contain many instances of such usage of APIs. However, conventional information retrieval techniques fail to perform well in retrieving API usage examples from code repositories. This paper presents Structural Semantic Indexing (SSI), a technique to associate words to source code entities based on similarities of API usage. The heuristic behind this technique is that entities (classes, methods, etc.) that show similar uses of APIs are semantically related because they do similar things. We evaluate the effectiveness of SSI in code retrieval by comparing three SSI based retrieval schemes with two conventional baseline schemes. We evaluate the performance of the retrieval schemes by running a set of 20 candidate queries against a repository containing 222,397 source code entities from 346 jars belonging to the Eclipse framework. The results of the evaluation show that SSI is effective in improving the retrieval of examples in code repositories.
Starting Page	157
Ending Page	166
Page Count	10
File Format	PDF
ISBN	9781605587912
DOI	10.1145/1882291.1882316
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-11-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Api usage Ssi Structural semantic indexing Code search Software information retrieval
Content Type	Text
Resource Type	Article

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