Engineering Trustworthy Software: A Mission for LLMs
Marco Vieira

TL;DR
This paper discusses how large language models can revolutionize software engineering by enhancing development processes, but emphasizes the need to address challenges like bias and explainability to ensure trustworthiness.
Contribution
It highlights the potential of LLMs in software engineering and identifies key challenges to achieving trustworthy AI-driven development.
Findings
LLMs can accelerate software development and improve bug detection.
Trustworthiness requires addressing bias, explainability, and scalability issues.
Integration of LLMs can transform the entire software lifecycle.
Abstract
LLMs are transforming software engineering by accelerating development, reducing complexity, and cutting costs. When fully integrated into the software lifecycle they will drive design, development and deployment while facilitating early bug detection, continuous improvement, and rapid resolution of critical issues. However, trustworthy LLM-driven software engineering requires addressing multiple challenges such as accuracy, scalability, bias, and explainability.
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Taxonomy
TopicsCloud Data Security Solutions · Scientific Computing and Data Management · Digital Rights Management and Security
