AI Software Engineer: Programming with Trust

• URL: http://arxiv.org/abs/2502.13767v1
• Date: Wed, 19 Feb 2025 14:28:42 GMT
• Title: AI Software Engineer: Programming with Trust
• Authors: Abhik Roychoudhury, Corina Pasareanu, Michael Pradel, Baishakhi Ray,
• Abstract summary: Large Language Models (LLMs) have shown surprising proficiency in generating code snippets.<n>We argue that successfully deploying AI software engineers requires a level of trust equal to or even greater than the trust established by human-driven software engineering practices.
• Score: 33.88230182444934
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large Language Models (LLMs) have shown surprising proficiency in generating code snippets, promising to automate large parts of software engineering via artificial intelligence (AI). We argue that successfully deploying AI software engineers requires a level of trust equal to or even greater than the trust established by human-driven software engineering practices. The recent trend toward LLM agents offers a path toward integrating the power of LLMs to create new code with the power of analysis tools to increase trust in the code. This opinion piece comments on whether LLM agents could dominate software engineering workflows in the future and whether the focus of programming will shift from programming at scale to programming with trust.

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