Formal Verification of Control System Software

Description

An essential introduction to the analysis and verification of control system software The verification of control system software is critical to a host of technologies and industries, from aeronautics and medical technology to the cars we drive. The failure of controller software can cost people their lives. In this authoritative and accessible book, Pierre-Loïc Garoche provides control engineers and computer scientists with an indispensable introduction to the formal techniques for analyzing and verifying this important class of software. Too often, control engineers are unaware of the issues surrounding the verification of software, while computer scientists tend to be unfamiliar with the specificities of controller software. Garoche provides a unified approach that is geared to graduate students in both fields, covering formal verification methods as well as the design and verification of controllers. He presents a wealth of new verification techniques for performing exhaustive analysis of controller software. These include new means to compute nonlinear invariants, the use of convex optimization tools, and methods for dealing with numerical imprecisions such as floating point computations occurring in the analyzed software. As the autonomy of critical systems continues to increase—as evidenced by autonomous cars, drones, and satellites and landers—the numerical functions in these systems are growing ever more advanced. The techniques presented here are essential to support the formal analysis of the controller software being used in these new and emerging technologies. Cover Formal Verification of Control System Software Copyright Contents Part I: Need and Tools to Verify Critical Cyber-Physical Systems 1 Critical Embedded Software 2 Formal Methods 3 Control Systems Part II: Invariant Synthesis: Convex-optimization Based Abstract Interpretation 4 Definitions—Background 5 Invariant Synthesis via Convex Op 6 Template-based Analyses and Min-policy Iteration Part III: System-level Analysis at Model and Code Level 7 System-level Properties as Numerical Invariants 8 Validation of System-level Properties at Code Level Part IV: Numerical Issues 9 Floating-point Semantics of Analyzed Programs 10 Convex Optimization and Numerical Issues Bibliography Index Acknowledgments