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Harnessing the Power of Large Language Models for Automated Code Generation and Verification

Unai Antero, Fernando Oleo Blanco, Jon Oñativia, Damien Sallé, Basilio Sierra

Year
2024
Citations
10
Access
Open access

Abstract

The cost landscape in advanced technology systems is shifting dramatically. Traditionally, hardware costs took the spotlight, but now, programming and debugging complexities are gaining prominence. This paper explores this shift and its implications, focusing on reducing the cost of programming complex robot behaviors, using the latest innovations from the Generative AI field, such as large language models (LLMs). We leverage finite state machines (FSMs) and LLMs to streamline robot programming while ensuring functionality. The paper addresses LLM challenges related to content quality, emphasizing a two-fold approach using predefined software blocks and a Supervisory LLM.

Keywords

Code generationComputer scienceProgramming languageCode (set theory)Software engineeringOperating system

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