A Methodology for Generating Mobile Applications Through Large Language Models

This repository contains the supplementary materials for our paper, titled "A Methodology for Generating Mobile Applications Through Large Language Models". In this work, we present and validate a platform-independent method for generating and evaluating complete mobile applications from high-level natural language descriptions. Our approach utilizes a multi-agent Large Language Model (LLM) framework to manage a three-stage process: App Description Generation, Code Generation, and Evaluation. 📂 Repository Structure This repository is organized into three main directories, corresponding to the stages of our methodology: ├── 1.app-description/ # Natural language app descriptions │ ├── boobie-goods.txt │ ├── duolingo.txt │ └── threads.txt ├── 2.app-generation/ # Generated mobile applications │ ├── boobie-goods.zip │ ├── duolingo.zip │ └── threads.zip ├── 3.evaluation/ # Research evaluation materials │ ├── boobie-goods.pdf │ ├── duolingo.pdf │ ├── threads.pdf │ └── legend.png └── README.md # This file 📝 How to Use This Repository 1. App Description The 1.app-description/ directory contains the detailed mobile app specification documents generated by the "product manager" LLM agent. These .txt files served as the blueprint for the code generation phase. Each file includes: App purpose: The main objective of the application. Detailed Feature List: A comprehensive list of functionalities. Layout and components: A description of the app's screens and UI elements. User interaction flow: A complete map of possible user journeys within the app. 2. App Generation The 2.app-generation/ directory contains the complete source code for the three mobile applications generated by our methodology. The applications were developed using the Flutter framework. To use these files: Unzip the desired application file (e.g., unzip boobie-goods.zip). Navigate into the project directory. Follow the standard procedure to build and run a Flutter application. 3. Evaluation The 3.evaluation/ directory contains the reports from our code quality assessment, which was performed using SonarQube. Each PDF file provides a detailed static analysis of the generated source code, focusing on: Reliability (Bugs) Security (Vulnerabilities) Maintainability (Code Smells) Duplications Complexity The legend.png file provides a key to understanding the ratings and metrics used in the SonarQube reports.