Code Smell Identification As The Basis For Code Refactoring in The Agricultural Information System Portal Case Study at: Gilangharjo Village, Bantul Regency, Indonesia
Journal: International Journal of Advanced Trends in Computer Science and Engineering (IJATCSE) (Vol.10, No. 3)Publication Date: 2021-06-11
Authors : Argo Wibowo Lukas Chrisantyo Maria Nila Anggia Rini;
Page : 1711-1719
Keywords : ;
Abstract
Nformation system technology continues to evolve over time. Various fields of science including agriculture also utilize information system to improve quality and services in the agricultural sector. Indonesia is an agrarian country where most of the populations work in the agricultural sector. Based on this fact, the Indonesian government is also very supportive towards improving and developing technology in agriculture. Dutatani is one of the Agricultural Information Systems (SIP) that has been consistently developed since 2016 towards precision agriculture. One of the technologies developed is web-based technology which has many sub-systems in it. This raises the problem regarding system scalability wherein each sub-system is developed separately and uses a different development model. Each system uses a specific framework and a native. Therefore this study aims to identify which sub-systems are suitable to be developed and refactored to become a new agricultural information system portal. The identification process used a code smell and metric-based approach. The metrics used were Line of Code (LOC), Complexity, Lack of Cohesion of Methods (LCOM) and God Class. From the results of detection using a code smell, the code detected was 55.17%. This study also revealed a fact that code with a good structure would be easier to detect. Modular code that used a framework and was orderly structured could be read well by detection tools, and showed a high LCOM rate compared to structured and nativecode
Other Latest Articles
- Domain Specific Model Driven Approach for Adaptive Systems
- Recognition of Human Face Emotions Detection Using Computer Vision Based Smart Images
- An Improved Methodology for Data Hiding In Images Using Haar Transformed, LSB Replacement Method and Modified PVDMF 1
- Covid Tracker for Medical Front-Liners- A Survey
- Performance Evaluation of Slotted Aloha Anti-Collision Protocol for Mobile RFID Tags Identification using NHPP
Last modified: 2021-06-11 19:36:44