AISQ 2026

In the era of Industry 4.0, advanced intelligent software applications, such as cyber-physical systems (CPS), machine learning-based systems, manufacturing systems, digital twin systems, quantum software applications, multi-agent systems, real-time systems and LLM-based systems, are playing an increasingly important role in both the industrial world and our daily lives. Failures or violations of these systems' requirements may lead to disruptive consequences, even catastrophic ones. For example, a collision involving an autonomous driving vehicle could result in human lives being lost. At the same time, the "hallucination" of an LLM-based AI advisor could mislead people into making wrong decisions, thereby causing large economic losses. Therefore, ensuring the quality of such systems is essential. Particularly, how to harness those advanced technologies, such as LLMs, which are versatile and flexible and can undertake various roles across different tasks, so that we can reap the benefits of automation and convenience while keeping their performance within safe and acceptable limits, is also highly meaningful.

Nowadays, extensive academic research, including both formal methods and engineering technologies, has been conducted to improve the quality of advanced intelligent software from various aspects, such as its usability, correctness, reliability, scalability, and robustness. However, these advanced systems tend to comprise multiple components or intelligent agents and perform complex tasks in ever-changing environments. Indeed, the rapid evolution of computer/AI technologies—particularly the recent breakthroughs in large language models and quantum computing—has precipitated a series of novel challenges in software quality assurance and dependability. New research topics and directions, such as prompt engineering and harness engineering, are constantly emerging. Our AISQ aims to bridge the gap between up-to-date systems with complex behaviours and the scalability of quality assurance techniques, approaches, methodologies, and fundamental theories. Specifically, AISQ seeks to collect promising and high-quality research achievements and provide an international venue to discuss the advanced discoveries and emerging trends related to the quality of Advanced Intelligent Software in both the academic society and the industrial world. This workshop will explore emerging theories and techniques for modelling and evaluating complex systems. Also, it will seek useful methods or tools to localise and fix system vulnerabilities.