On the feasibility of detecting cross-platform code clones via identifier similarity

Xiao Cheng, Lingxiao Jiang, Hao Zhong, Haibo Yu, Jianjun Zhao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

More and more mobile applications run on multiple mobile operating systems to attract more users of different platforms. Although versions on different platforms are implemented in different programming languages (e.g., Java and Objective-C), there must be many code snippets that implement the similar business logic on different platforms. Such code snippets are called cross-platform clones. It is challenging but essential to detect such clones for software maintenance. Due to the practice that developers usually use some common identifiers when implementing the same business logic on different platforms, in this paper, we investigate the identifier similarity of the same mobile application on different platforms and provide insights about the feasibility of cross-platform clone detection via identifier similarity. In our experiment, we have analyzed the source code of 18 open-source cross-platform applications which are implemented on Android, iOS and Windows Phone, and find that the smaller KL-Divergence the application has, the more accurate the clones detected by identifiers will be.

Original languageEnglish
Title of host publicationSoftwareMining 2016 - Proceedings of the 5th International Workshop on Software Mining, co-located with ASE 2016
EditorsLucia Lucia, Ming Li, Xiaoyin Wang
PublisherAssociation for Computing Machinery, Inc
Pages39-42
Number of pages4
ISBN (Print)9781450345118
DOIs
Publication statusPublished - Sep 3 2016
Event5th International Workshop on Software Mining, SoftwareMining 2016 - co-located with ASE 2016 - Singapore, Singapore
Duration: Sep 3 2016 → …

Publication series

NameSoftwareMining 2016 - Proceedings of the 5th International Workshop on Software Mining, co-located with ASE 2016

Other

Other5th International Workshop on Software Mining, SoftwareMining 2016 - co-located with ASE 2016
CountrySingapore
CitySingapore
Period9/3/16 → …

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All Science Journal Classification (ASJC) codes

  • Software
  • Computational Theory and Mathematics

Cite this

Cheng, X., Jiang, L., Zhong, H., Yu, H., & Zhao, J. (2016). On the feasibility of detecting cross-platform code clones via identifier similarity. In L. Lucia, M. Li, & X. Wang (Eds.), SoftwareMining 2016 - Proceedings of the 5th International Workshop on Software Mining, co-located with ASE 2016 (pp. 39-42). (SoftwareMining 2016 - Proceedings of the 5th International Workshop on Software Mining, co-located with ASE 2016). Association for Computing Machinery, Inc. https://doi.org/10.1145/2975961.2975967