QRS 2024 Conference - IEEE International Conference on Software Security and Reliability

About QRS

In 2015, the SERE conference (IEEE International Conference on Software Security and Reliability) and the QSIC conference (IEEE International Conference on Quality Software) were combined into a single conference, QRS, with Q representing Quality, R for Reliability, and S for Security, sponsored by the IEEE Reliability Society. This conference gives engineers and scientists from both industry and academia a platform to present their ongoing work, relate their research outcomes and experiences, and discuss the best and most efficient techniques for the development of reliable, secure, and trustworthy systems. It also provides an excellent opportunity for the academic community to become more aware of subject areas critical to the software industry as practitioners bring their needs to the table. The 24th QRS conference will be held from July 1-5, 2024 in Cambridge, United Kingdom.

News & Announcements

Platinum Sponsor

Huawei Technologies Co., Ltd.

Keynote Speaker

Keynote 1: TBA

Keynote 2: TBA

Topics of Interest

• Reliability, Security, Availability, and Safety of Software Systems
• AI-based Techniques for Software Quality, Reliability, and Security
• Knowledge-based Techniques for Software Quality, Reliability, and Security
• Software Testing, Verification, and Validation
• Program Debugging and Comprehension
• Information and Software Quality Assurance
• Fault Tolerance for Software Reliability Improvement
• Modeling, Prediction, Simulation, and Evaluation
• Metrics, Measurements, and Analysis
• Secure and Reliable Storage
• Software Penetration and Protection
• Software Vulnerabilities
• Formal Methods
• Malware Detection and Analysis
• Intrusion Detection and Prevention
• Operating System Security and Reliability
• Mobile and Smartphone Applications
• Internet of Things and Cloud Computing
• Information and Knowledge Management
• Benchmark, Tools, Industrial Applications, and Empirical Studies
• Machine Learning and Deep Learning Models and Systems