Abstract—Different types of codes which may increase the
liability of bugs or defects in future to a system known as Code
smell. These type of smell can be eliminated without changing
the external outcome and modifying the internal structure of
the system. There are existing several well known code smell
detection tools which automatically identify the code smells.
The research used PMD automatic code smell detector to find
four code smells on various open source java projects. It uses
43 open source java projects and identify the selective smells to
these projects. The experiment shows duplicate codes, unused
imports, unused local variables and unused private methods
are not present for 79%, 34.9%, 51.1%, and 86.04% projects
respectively. In the paper, it also shows that the probability of
occurring duplicate codes, unused imports, unused local
variables and unused private methods are respectively 4.5%,
71%, 20.4% and 4.1% which indicates the four selective code
smells are declining in real life projects day by day.
Index Terms—Code smell, refactoring, detector and PMD.
The authors are with Computer Science and Engineering, University of
Barisal, Barisal, Bangladesh (e-mail: sams.csebu@gmail.com,
mostafij.csebu@gmail.com, irfan.bucse@gmail.com,
bohnishikha46@gmail.com, sathibucse08@gmail.com,
shariful.islam@gmail.com, rhfaisal@gmail.com).
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Cite:Md. Erfan, Bohnishikhan Halder, Sathi Rani Pal, Md. Shariful Islam, and Rahat Hossain Faisal, "Experimental Study of Four Selective Code Smells Declining in Real Life Projects," International Journal of Information and Electronics Engineering vol. 8, no. 4, pp. 46-49, 2018.
