DOI : https://doi.org/10.18517/ijaseit.10.3.10182

Zsmell – Code Smell Detection for Open Source Software

Aziz Nanthaamornphong (1), Tanawat Saeang (2), Panyaprach Tularak (3)
(1) College of Computing, Prince of Songkla University, Phuket Campus, Kathu, 83120, Thailand
(2) College of Computing, Prince of Songkla University, Phuket Campus, Kathu, 83120, Thailand
(3) College of Computing, Prince of Songkla University, Phuket Campus, Kathu, 83120, Thailand
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How to cite (IJASEIT) :
Nanthaamornphong, Aziz, et al. “Zsmell – Code Smell Detection for Open Source Software”. International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 3, June 2020, pp. 1035-41, doi:10.18517/ijaseit.10.3.10182.
Citation Format :
Today, open-source software (OSS) is used in various applications. It has played a vital role in information systems of many user groups such as commercials, research, education, public health, and tourism. It is also a source of additional knowledge for collaborators because this type of software is easily accessible through websites that provide management of version control services such as GitHub. However, a recent study shows an increasing trend in the existence of code smells. In OSS, there is a growing number of code smells that cause software errors. Having a code smell in software is a serious issue since it impacts the software in terms of deployment, maintenance as well as user confidence toward the software. Finding code smells in the early stages of software development would provide for better software maintenance and reliability; thus, researchers invented the Zsmell software system that helps search for code smells in the source code saved in GitHub. Developed systems display data related to code smells in each source code version that was modified by collaborators. Thus, the developers will be able to employ the proper refactoring method, which is a change in the internal structure of software without changing the original functionality of the software. We believe that this system will enable open source collaborators to improve the quality of their OSS, especially on code smell reduction and the understanding of various types of code smell commonly found in OSS projects.

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