Author: Priya Singhaniya , Rahul Chaurasia
Abstract: The rapid growth of mobile applications has increased the demand for efficient Android development. Traditional coding practices often involve repetitive tasks, boilerplate code, and high potential for human error. AI-assisted code generation, leveraging machine learning (ML) and natural language processing (NLP) models, provides an innovative solution to these challenges by automating code writing, error detection, and optimization. This paper reviews the current state of AI-assisted code generation in Android development, analyzing various AI tools, techniques, and frameworks, and evaluates their impact on productivity, code quality, and developer experience. We also explore challenges, such as model limitations, security concerns, and ethical considerations, and suggest potential future directions to enhance AIdriven development processes.
Keywords: AI-assisted code generation, Android development, machine learning, code automation, deep learning, natural language processing, mobile application development
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