Mobile Application Performance Improvement with the Implementation of Code Refactor Based on Code Smells Identification: Dutataniku Agriculture Mobile App Case Study

Wibowo, Argo; Chrismanto, Antonius Rachmat; Rini, Maria Nila Anggia; Chrisantyo, Lukas

doi:10.1109/icic56845.2022.10006961

Cited by 2 publications

(3 citation statements)

References 33 publications

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“…Furthermore, a research gap regarding code smells exists between the identification of code smells based on previous studies and the characterization of code smells through the SonarQube tool, because code smells based SonarQube tool has not been studied on the resource usage in mobile applications. Therefore, our study focuses on the resource usage with metric CPU usage and memory usage, similar to the study by Oliveira et al [1], Alkandari et al [11], and Wibowo et al [15]. For measures intensity ratio of code smells our study using FDR metric, is also similarly to the study conducted by Etemadi Someoliayi, et al [19].…”

Section: Introductionmentioning

confidence: 81%

“…The rapid consumption in applications can cause users to switch or uninstall the application from their device. However, the previous research on code smells related to resource usage has not fully explored the issue and has mainly used emulators [11], [14], [15]. It is important to note that behavior of an emulator differs from that of a physical device [1].…”

Section: Introductionmentioning

confidence: 99%

“…Wibowo, et al [15] discusses two code smells i.e., noequal-then-else and prefer-conditional-expressions on one application. This study discusses problem code smells impact to performance in agricultural mobile applications.…”

Section: Introductionmentioning

confidence: 99%

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

Syawanodya,

Anggraini,

Al-Hijri

et al. 2024

Int. J. Adv. Sci. Eng. Inf. Technol.

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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.

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