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Exploring the performance gap: How animation implementation affects the CPU and RAM usage in mobile applications: Among cross-platform and native development approaches
2023 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Mobile applications are a critical part of everyday life. Animations in mobile applications demand optimized performance, which developers are persistently striving to achieve. This study examines the performance of mobile applications developed using native approaches for iOS and Android, as well as the Flutter framework for cross-platform approach, while executing animations. This was motivated by the fact that while cross-platform development offers advantages in terms of development efficiency, it often results in decreased performance. Since the field of mobile development is continuously evolving, it is important to explore new capabilities of mobile technologies.

The purpose of this study is to understand the differences in CPU and RAM usage between native and cross-platform applications by examining two types of animation implementations, thereby aiming to identify the causes of the performance gap and propose solutions to decrease the performance gap. This study involved experiments, a literature study and an analysis of the results to address the research questions and fulfill the purpose.

The findings of this study showed that the cross-platform approach resulted in higher CPU and RAM usage than the native approaches. However, the performance gap was less noticeable in one of the animation implementations. Thus indicating that the performance of mobile applications can be significantly influenced by the choice of animation implementation. Therefore, a strategic approach to mitigating the performance gap could involve careful selection of Flutter widgets or the incorporation of efficient libraries.

Place, publisher, year, edition, pages
2023. , p. 91
Keywords [en]
animations, app development, cross-platform, Flutter, mobile development, performance
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:hj:diva-62029ISRN: JU-JTH-DTA-1-20230198OAI: oai:DiVA.org:hj-62029DiVA, id: diva2:1783215
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Etteplan
Subject / course
JTH, Computer Engineering
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Available from: 2023-08-08 Created: 2023-07-19 Last updated: 2023-08-08Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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