IoTCoder: A Copilot for IoT Application Development

Existing code Large Language Models are primarily designed for generating simple and general algorithms but are not dedicated to IoT applications. To fill this gap, we present IoTCoder, a coding copilot specifically designed to synthesize programs for IoT application development. IoTCoder features three locally deployed small language models (SLMs): a Task Decomposition SLM that decomposes a complex IoT application into multiple tasks with detailed descriptions, a Requirement Transformation SLM that converts the decomposed tasks described in natural language to well-structured specifications, and a Modularized Code Generation SLM that generates modularized code based on the task specifications. Experiment results show that IoTCoder can synthesize programs adopting more IoT-specific algorithms and outperform state-of-the-art code LLMs in terms of both task accuracy (by more than 24.2% on average) and memory usage (by less than 358.4 MB on average).