Nabilah
ABSTRACT
Software change is inevitable, evolution becomes a part of software lifetime, and software release becomes more frequent. Hence there is a need for the project manager to inspect and control the process during software development and evolution. In the evolutionary stage, developers will face problems related to program code, one of that is identification of code smells. This problem could negatively affect maintainability in evolution, a developer needs more time and money. Visualization techniques turn data into a visual form so that it can provide information that is easier to understand. In software evolution, visualization mostly is used to view structure code. Previous research on evolution visualization limited to visualize the addition of code, the last update, release history, and information of developer that made the last change in program. However, this visualization is not enough to support understanding for the developers. We propose a visualization method for identifying code smell of the evolution software on java programming, so the developers can more easily understand the code that will be evolved. By knowing where the smell of code in the program, programmers can immediately do refactoring, the time and costs needed will also be low. Visualization of code smell is something new in the domain of software evolution. Finally, this design created to build tools in detecting code smells for software evolution process control.
- Diehl, S. 2010. Software Visualization: Visualizing the Structure, Behaviour, and Evolution of Software, Springer, Heidelberg. Google Scholar
Digital Library
- Jabangwe, R. 2012. An Exploratory Study of Software Evolution and Quality: Before, During and After a Transfer.Google Scholar
- Pereira, R., Oliveira, D., Rodrigues, A., Santana, E., and Almeida, D. 2016. Evaluating Lehman ' s Laws of software evolution within software product lines industrial projects, 0, 1--19. Google ScholarDigital Library
- Kaur, K. 2012. Process and Product Metrics to Assess Quality of Software Evolution, 36--41.Google Scholar
- Lima, R., Torres, A., Souto, T., Mendonça, M., and Zazworka, N. 2013. Software evolution visualization: A systematic mapping study, Information and Software Technology, 55(11), 1860--1883. Google ScholarDigital Library
- Fowler, M., Beck, K., Brant, J., and Opdyke, W. 2002. Refactoring: Improving the Design of Existing Code.Google ScholarCross Ref
- Brown, L. D., Hua, H., and Gao, C. 2003. A widget framework for augmented interaction in SCAPE. In Proceedings of the 16th Annual ACM Symposium on User Interface Software and Technology (Vancouver, Canada, November 02-05, 2003). UIST '03. ACM, New York, NY, 1--10. Google ScholarDigital Library
- Salameh, H. B., and Aljammal, A. 2016. Software Evolution Visualization Techniques and Methods - a Systematic Review, 1--6.Google Scholar
- Fontana, Francesca Arcelli., Zanoni, Marco.2018. A large-scale empirical study on the lifecycle of code smell co-occurrences.Google Scholar
- Gall, Harald C., Lanza, Michele. Software Evolution: Analysis and VisualizationGoogle Scholar
- Lehman, M M., Perry, D E., Ramil, JF. 1998. Implication of Evolution Metrics on Software Maintenance.Google Scholar
- Chapin, Ned., Hale, Joanne E., Khan, Khaled., Ramil, Juan F., Tan, Wui Gee. 2001. Types of SOdtware Evolution and Software Maintenance.Google Scholar
- Mens, Tom. 2008. Software Evolution. Google ScholarDigital Library
- Santos, Jose Amancio M., Rocha-junior, Joao B., Carla. 2018. The Journal of Systems & Software a Systematic Review on The Code Smell Effect. 450--477.Google Scholar
- Lanza, Michele. The Evolution Matrix: Recovering Software Evolution using Software Visualization Techniques.Google Scholar
- Walter, B., Arcelli, F., Ferme, V. 2018. Code Smells and their collocation: A large-scale experiment on open-source systems.Google Scholar
- Ilyas, M., Palomba, F., Shi, L., Wang, Q. 2019. Machine learning techniques for code smell detection: A systematic literature review and meta-analysis. 115--138.Google Scholar
- Hozano, M., Garcia, A., Fonseca, B. 2018. Are you smelling it? Investigating how similar developers detect code smells. 130--146. Google ScholarDigital Library
- Singh, S., Kaur, S. 2018. A systematic literature review: Refactoring for disclosing code smells in object oriented software.Google Scholar
Index Terms
- Controlling Software Evolution Process Using Code Smell Visualization
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