Mining API Usage Patterns by Applying Method Categorization to Improve Code Completion
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- AKBAR Rizky Januar
- Graduate School of Science and Engineering, Ritsumeikan University
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- OMORI Takayuki
- Department of Computer Science, Ritsumeikan University
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- MARUYAMA Katsuhisa
- Department of Computer Science, Ritsumeikan University
Abstract
Developers often face difficulties while using APIs. API usage patterns can aid them in using APIs efficiently, which are extracted from source code stored in software repositories. Previous approaches have mined repositories to extract API usage patterns by simply applying data mining techniques to the collection of method invocations of API objects. In these approaches, respective functional roles of invoked methods within API objects are ignored. The functional role represents what type of purpose each method actually achieves, and a method has a specific predefined order of invocation in accordance with its role. Therefore, the simple application of conventional mining techniques fails to produce API usage patterns that are helpful for code completion. This paper proposes an improved approach that extracts API usage patterns at a higher abstraction level rather than directly mining the actual method invocations. It embraces a multilevel sequential mining technique and uses categorization of method invocations based on their functional roles. We have implemented a mining tool and an extended Eclipse's code completion facility with extracted API usage patterns. Evaluation results of this tool show that our approach improves existing code completion.
Journal
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- IEICE Transactions on Information and Systems
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IEICE Transactions on Information and Systems E97.D (5), 1069-1083, 2014
The Institute of Electronics, Information and Communication Engineers
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Details 詳細情報について
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- CRID
- 1390282679356766080
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- NII Article ID
- 130004519222
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- ISSN
- 17451361
- 09168532
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed