Engineering Open-Source Applications Leveraging Diverse Scripting and Coding Practices for Mobile and Android Platforms

Abstract

The rapid evolution of mobile and Android applications has been significantly influenced by open-source development, leveraging diverse scripting and coding practices to enhance performance, security, and user engagement. This study explores the impact of various programming languages, including Java, Kotlin, Python, JavaScript (React Native), and Dart (Flutter), on mobile application efficiency. A mixed-methods approach was employed, integrating qualitative content analysis of open-source repositories with quantitative statistical modeling. The findings indicate that programming languages significantly affect execution time and memory consumption, with Kotlin exhibiting superior performance. Security vulnerabilities emerged as a critical factor negatively correlating with user engagement (-0.61, p=0.002), emphasizing the need for secure coding practices. Code complexity also played a role in application maintainability, with higher complexity associated with reduced efficiency. Machine learning models, particularly Random Forest and Neural Networks, demonstrated high accuracy (89.2% and 91.4%, respectively) in predicting application success, with community engagement and security vulnerabilities being the most influential factors. These insights underscore the importance of efficient scripting, security-first development, and active community contributions in open-source mobile engineering. The study provides actionable recommendations for developers to optimize coding strategies for improved application performance and adoption.