Artificial Intelligence for Software Engineering: From Probable to Provable

Speaker:  Bertrand Meyer – Zurich, Switzerland
Topic(s):  Human Computer Interaction , Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing , Software Engineering and Programming , Computational Theory, Algorithms and Mathematics , Society and the Computing Profession , Applied Computing

Abstract

This lecture addresses the fundamental paradigm shift in software construction introduced by Large Language Models (LLMs). While AI provides "probable" solutions through statistical inference, the critical nature of software—especially in mission-critical systems—demands the "provable" guarantees of formal verification. The presentation explores the risks of "hallucination loops" in AI-assisted programming and Automatic Program Repair (APR), as identified in 2025 empirical studies. It proposes a rigorous framework where AI acts as a generator of candidates, which are then strictly validated through Design by Contract (DbC) and formal methods. The goal is to move from the "stochastic parrot" model of coding to a hybrid approach of "AI-assisted formal software engineering."

About this Lecture

Number of Slides:  30
Duration:  minutes
Languages Available:  English, French, German, Italian, Russian
Last Updated:  27/02/2026

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