What is it about?
Software maintenance, which involves fixing bugs and improving performance, is a significant part of software development and can be very costly. Our research explores using AI-powered agents to automate these maintenance tasks. These intelligent agents, which are powered by large language models, can learn from their interactions with software to identify and fix problems. This not only reduces the need for human intervention but also improves the quality and reliability of the software. Our goal is to create tools that make software maintenance more efficient and less expensive, ultimately making better software available to everyone.
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Why is it important?
Our research is significant because it addresses one of the most costly and labor-intensive aspects of software development: maintenance. By introducing AI-powered agents capable of autonomously identifying and fixing software issues, we developing approaches that could help software developers in their daily lives. This technology is particularly timely given the exponential growth of software code and the increasing complexity of software systems. Our work promises to enhance the quality and reliability of software, reduce costs, and free up human developers to focus on more creative and strategic tasks. This could lead to faster innovation cycles and more robust software applications, benefiting businesses and users.
Perspectives
Writing this article has been a rewarding experience, as it represents a significant step forward in my quest to improve software development. I am passionate about reducing the tedious burden of software maintenance. I hope this research brings more attention to the potential of LLM-based agents. While many researchers focus on using bigger models, which is not sustainable, my aim is to understand why agents work so well. I believe this approach will inspire others to explore AI-powered agents further and spark innovation in sustainable, efficient software development.
Fernando Vallecillos Ruiz
Simula Research Laboratory
Read the Original
This page is a summary of: Agent-Driven Automatic Software Improvement, June 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3661167.3661171.
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