Mining API Usage Patterns by Applying Method Categorization to Improve Code Completion

Rizky Januar AKBAR; Takayuki OMORI; Katsuhisa MARUYAMA

doi:10.1587/transinf.E97.D.1069

Mining API Usage Patterns by Applying Method Categorization to Improve Code Completion

Rizky Januar AKBAR, Takayuki OMORI, Katsuhisa MARUYAMA

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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.

Publication: IEICE TRANSACTIONS on Information Vol.E97-D No.5 pp.1069-1083

Publication Date: 2014/05/01

Publicized

Online ISSN: 1745-1361

DOI: 10.1587/transinf.E97.D.1069

Type of Manuscript: Special Section PAPER (Special Section on Knowledge-Based Software Engineering)

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Authors

Rizky Januar AKBAR
  Ritsumeikan University
Takayuki OMORI
  Ritsumeikan University
Katsuhisa MARUYAMA
  Ritsumeikan University

Keyword

sequential pattern mining, software repositories, recommendation, code completion

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Rizky Januar AKBAR, Takayuki OMORI, Katsuhisa MARUYAMA, "Mining API Usage Patterns by Applying Method Categorization to Improve Code Completion" in IEICE TRANSACTIONS on Information, vol. E97-D, no. 5, pp. 1069-1083, May 2014, doi: 10.1587/transinf.E97.D.1069.
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.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.E97.D.1069/_p

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@ARTICLE{e97-d_5_1069,
author={Rizky Januar AKBAR, Takayuki OMORI, Katsuhisa MARUYAMA, },
journal={IEICE TRANSACTIONS on Information},
title={Mining API Usage Patterns by Applying Method Categorization to Improve Code Completion},
year={2014},
volume={E97-D},
number={5},
pages={1069-1083},
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.},
keywords={},
doi={10.1587/transinf.E97.D.1069},
ISSN={1745-1361},
month={May},}

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TY - JOUR
TI - Mining API Usage Patterns by Applying Method Categorization to Improve Code Completion
T2 - IEICE TRANSACTIONS on Information
SP - 1069
EP - 1083
AU - Rizky Januar AKBAR
AU - Takayuki OMORI
AU - Katsuhisa MARUYAMA
PY - 2014
DO - 10.1587/transinf.E97.D.1069
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E97-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2014
AB - 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.
ER -