QRS 2025 Plenary Panel I

Rethinking Software Quality, Reliability, and Security in the Era of AI and LLMs


Opening Lines


AI and Large Language Models (LLMs) are rapidly transforming the software engineering landscape— from assisting developers with real-time code suggestions to autonomously detecting bugs and vulnerabilities. These technologies promise to automate labor-intensive tasks, enhance test coverage, and boost productivity. But their adoption also raises critical concerns: hallucinated code, hidden biases, unclear provenance, and emergent security risks. As AI becomes both a co-pilot and a code contributor, how do we harness its potential to improve software quality, reliability, and security— without introducing new fault lines?

Panel Scope


This panel brings together experts across research and practice to explore:

Audience Engagement Hook


We will explore the full spectrum— from promise to pitfalls— with timely questions such as:

Moderator


David Lo's avatar
Professor David Lo Singapore

Singapore Management University


Panelists (Alphabetical Order)


Xiaoxing Ma's avatar
Professor Xiaoxing Ma China

Nanjing University


Kai Pan's avatar
Dr. Kai Pan China

Architect of Quality & Efficiency Department of Technology Platform

Baidu Inc.


Tong Shen's avatar
Dr. Tong Shen China

Senior Engineer

Huawei Technologies Co., Ltd.


Hailong Sun's avatar
Professor Hailong Sun China

Beihang University


Xin Xia's avatar
Professor Xin Xia China

Zhejiang University


Zheng Zheng's avatar
Professor Zheng Zheng China

Beihang University