Analyzing System Performance with Formal Models

Ever wonder if a system can truly handle its maximum expected load without failing? Go beyond traditional testing and learn to mathematically prove the performance limits of complex systems, ensuring they are both reliable and efficient. This course provides a foundational understanding of quantitative formal modeling, a powerful technique for analyzing system behavior. You will learn to translate system descriptions into precise mathematical models and apply analytical methods to determine their worst-case performance, such as maximum latency or required buffer sizes. What you'll learn: - Understand the core principles of formal modeling and its role in system design and verification. - Learn to represent system behavior using foundational formalisms like Petri nets. - Apply mathematical techniques, including counting functions and prefix orders, to analyze your models. - Calculate worst-case performance metrics to guarantee system reliability under specific conditions. - Analyze concurrency, resource contention, and potential deadlocks in distributed systems. - Build a solid foundation for exploring automated verification and formal methods tools. The course begins with the essential theory behind system modeling, then progresses to hands-on written exercises where you will construct and analyze models for various scenarios. This course is designed for computer science students, software developers, and systems engineers. No prior experience with formal methods is required, but a comfort with abstract concepts is beneficial. Start your journey into the rigorous world of performance analysis and verification.