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There are already many books on formal verification, from academic to application-centric, and from tutorials for beginners to guides for advanced users. Many are excellent for their intended purpose; we recommend a few at the end of this book. But most start from the assumption that you have already committed to becoming a hands-on expert (or in some cases that you already are an expert). We feel that detailed tutorials are not the easiest place to extract the introductory view many of us are looking for - background, a general idea of how methods work, applications and how formal verification is managed in the overall verification objective. Since we're writing for a fairly wide audience, we cover some topics that some of you may consider elementary (why verification is hard), some we hope will be of general interest (elementary understanding of the technology) and others that may not immediately interest some readers (setting up a formal verification team). What we intentionally do not cover at all is how to become a hands-on expert.
Advances in scientific computing have made modelling and simulation an important part of the decision-making process in engineering, science, and public policy. This book provides a comprehensive and systematic development of the basic concepts, principles, and procedures for verification and validation of models and simulations. The emphasis is placed on models that are described by partial differential and integral equations and the simulations that result from their numerical solution. The methods described can be applied to a wide range of technical fields, from the physical sciences, engineering and technology and industry, through to environmental regulations and safety, product and plant safety, financial investing, and governmental regulations. This book will be genuinely welcomed by researchers, practitioners, and decision makers in a broad range of fields, who seek to improve the credibility and reliability of simulation results. It will also be appropriate either for university courses or for independent study.
Based on the highly successful second edition, this extended edition of SystemVerilog for Verification: A Guide to Learning the Testbench Language Features teaches all verification features of the SystemVerilog language, providing hundreds of examples to clearly explain the concepts and basic fundamentals. It contains materials for both the full-time verification engineer and the student learning this valuable skill. In the third edition, authors Chris Spear and Greg Tumbush start with how to verify a design, and then use that context to demonstrate the language features, including the advantages and disadvantages of different styles, allowing readers to choose between alternatives. This textbook contains end-of-chapter exercises designed to enhance students’ understanding of the material. Other features of this revision include: New sections on static variables, print specifiers, and DPI from the 2009 IEEE language standard Descriptions of UVM features such as factories, the test registry, and the configuration database Expanded code samples and explanations Numerous samples that have been tested on the major SystemVerilog simulators SystemVerilog for Verification: A Guide to Learning the Testbench Language Features, Third Edition is suitable for use in a one-semester SystemVerilog course on SystemVerilog at the undergraduate or graduate level. Many of the improvements to this new edition were compiled through feedback provided from hundreds of readers.
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.
This handy reference introduces the subject of forecastverification and provides a review of the basic concepts,discussing different types of data that may be forecast. Each chapter covers a different type of predicted quantity(predictand), then looks at some of the relationships betweeneconomic value and skill scores, before moving on to review the keyconcepts and summarise aspects of forecast verification thatreceive the most attention in other disciplines. The book concludes with a discussion on the most importanttopics in the field that are the subject of current research orthat would benefit from future research. An easy to read guide of current techniques with real life casestudies An up-to-date and practical introduction to the differenttechniques and an examination of their strengths andweaknesses Practical advice given by some of the world?s leadingforecasting experts Case studies and illustrations of actual verification and itsinterpretation Comprehensive glossary and consistent statistical andmathematical definition of commonly used terms
Static analysis of software with deductive methods is a highly dynamic field of research on the verge of becoming a mainstream technology in software engineering. It consists of a large portfolio of - mostly fully automated - analyses: formal verification, test generation, security analysis, visualization, and debugging. All of them are realized in the state-of-art deductive verification framework KeY. This book is the definitive guide to KeY that lets you explore the full potential of deductive software verification in practice. It contains the complete theory behind KeY for active researchers who want to understand it in depth or use it in their own work. But the book also features fully self-contained chapters on the Java Modeling Language and on Using KeY that require nothing else than familiarity with Java. All other chapters are accessible for graduate students (M.Sc. level and beyond). The KeY framework is free and open software, downloadable from the book companion website which contains also all code examples mentioned in this book.
Formal Verification: An Essential Toolkit for Modern VLSI Design, Second Edition presents practical approaches for design and validation, with hands-on advice to help working engineers integrate these techniques into their work. Formal Verification (FV) enables a designer to directly analyze and mathematically explore the quality or other aspects of a Register Transfer Level (RTL) design without using simulations. This can reduce time spent validating designs and more quickly reach a final design for manufacturing. Building on a basic knowledge of SystemVerilog, this book demystifies FV and presents the practical applications that are bringing it into mainstream design and validation processes. New sections cover advanced techniques, and a new chapter, The Road To Formal Signoff, emphasizes techniques used when replacing simulation work with Formal Verification. After reading this book, readers will be prepared to introduce FV in their organization to effectively deploy FV techniques that increase design and validation productivity.
This book describes in detail all required technologies and methodologies needed to create a comprehensive, functional design verification strategy and environment to tackle the toughest job of guaranteeing first-pass working silicon. The author first outlines all of the verification sub-fields at a high level, with just enough depth to allow an engineer to grasp the field before delving into its detail. He then describes in detail industry standard technologies such as UVM (Universal Verification Methodology), SVA (SystemVerilog Assertions), SFC (SystemVerilog Functional Coverage), CDV (Coverage Driven Verification), Low Power Verification (Unified Power Format UPF), AMS (Analog Mixed Signal) verification, Virtual Platform TLM2.0/ESL (Electronic System Level) methodology, Static Formal Verification, Logic Equivalency Check (LEC), Hardware Acceleration, Hardware Emulation, Hardware/Software Co-verification, Power Performance Area (PPA) analysis on a virtual platform, Reuse Methodology from Algorithm/ESL to RTL, and other overall methodologies.
Over the past decade, a number of hardware and software advances have conspired to thrust deep learning and neural networks to the forefront of computing. Deep learning has created a qualitative shift in our conception of what software is and what it can do: Every day we're seeing new applications of deep learning, from healthcare to art, and it feels like we're only scratching the surface of a universe of new possibilities. This book offers the first introduction of foundational ideas from automated verification as applied to deep neural networks and deep learning. It is divided into three parts: Part 1 defines neural networks as data-flow graphs of operators over real-valued inputs. Part 2 discusses constraint-based techniques for verification. Part 3 discusses abstraction-based techniques for verification. The book is a self-contained treatment of a topic that sits at the intersection of machine learning and formal verification. It can serve as an introduction to the field for first-year graduate students or senior undergraduates, even if they have not been exposed to deep learning or verification.