An Empirical Evaluation on the Effect Refactoring Code Smells Mobile Applications Android with ASATs on Resource Usage

Abstract

The Application is closely connected to mobile devices designed for many people and has maintenance, but even maintenance can contain violations such as code smells that effect non-functional requirements, specifically the use of CPU and memory resources. When the software has a rapid use of resources, it gives rise to the phenomenon that the user may switch or uninstall the software. The solution to this phenomenon is to explore resource-related code smells and fix them by refactoring. Developments to explore code smells came with ASATs, namely SonarQube, which is already being used by 85,000 organizations to speed up analyzing code in software. This topic is related to code smells, and the research objective is to analyze and compare the performance of the original versions and single or cumulative refactored versions of Android mobile software using the Design Research Methodology (DRM) approach. Types of code smells are represented based on the classification on SonarQube, namely Blocker, Critical, Major, and Minor, with code smells such as HashMap Usage, Member Ignoring Method, and Slow Loop. Aspects tested include Fixed Detection Ratio (FDR), improvement, CPU, and memory usage. Based on the results of the research, it shows the depreciation of code smells which is proven to significantly increase CPU performance in a single refactoring, namely Member Ignoring Method and Critical by 7.7% and 9.90%, respectively. Moreover, single refactoring offers developers advantages reducing high costs, diminished exertion, and truncated maintenance duration. However, the cumulative refactoring occasionally endeavors hold the potential be high improvements.