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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Clone Detection Techniques for JavaScript and Language Independence: Review

Author 1: Danyah Alfageh Author 2: Hosam Alhakami Author 3: Abdullah Baz Author 4: Eisa Alanazi Author 5: Tahani Alsubait
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 11, No. 4 · Published 2020

DOI: https://doi.org/10.14569/IJACSA.2020.01104102

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Abstract

Code clone detection is an active field of study in computer science. Despite its rich history, it lacks focus on web scripting languages. Due to the expansion of web applications and web development amongst developers of varying education and experience levels, they inevitably resort to cloning through out the web. The spread of code clones is further increased by websites like StackOverflow and GitHub. In this paper, we will be focusing on clone detection research done to target clones in JavaScript code and discuss its areas of concern. Also, we will summarize language independent research done and possibility of its application on JavaScript and web applications.

Keywords

Clone detection code clones JavaScript language independent clone detection web applications

How to Cite this Article

Alfageh, D., Alhakami, H., Baz, A., Alanazi, E., & Alsubait, T. (2020). Clone Detection Techniques for JavaScript and Language Independence: Review. International Journal of Advanced Computer Science and Applications, 11(4). https://doi.org/10.14569/IJACSA.2020.01104102

Alfageh, Danyah, et al.. "Clone Detection Techniques for JavaScript and Language Independence: Review." International Journal of Advanced Computer Science and Applications, vol. 11, no. 4, 2020, https://doi.org/10.14569/IJACSA.2020.01104102.

@article{Alfageh2020,
  title     = {Clone Detection Techniques for JavaScript and Language Independence: Review},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {4},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Danyah Alfageh and Hosam Alhakami and Abdullah Baz and Eisa Alanazi and Tahani Alsubait},
  doi       = {10.14569/IJACSA.2020.01104102},
  url       = {https://doi.org/10.14569/IJACSA.2020.01104102}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

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