Download e-book for kindle: Constraint-Based Verification by Jun Yuan

By Jun Yuan

ISBN-10: 0387259473

ISBN-13: 9780387259475

ISBN-10: 0387307842

ISBN-13: 9780387307848

Constraint-Based Verifcation covers the rising box in practical verification of digital designs thats is now in general mentioned through this name.

Topics are built within the context of a variety of dynamic and static verification ways together with stimulation, emulation and formal equipment. The aim is to teach how constraints, or assertions, can be utilized towards automating the new release of testbenches, leading to a unbroken verifcation stream. subject matters similar to verification assurance, and reference to assertion-based verification also are covered.

Constraint-Based Verification is written for verification engineers, in addition to researchers - it explains either methodological and technical matters. specific tension is given to the newest advances in sensible verification.

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Extra resources for Constraint-Based Verification

Sample text

Over-constraints stall the progress in simulation and lead to vacuous proofs in formal verification. Constraint diagnosis identifies the source of and helps to fix over-constraints. 7 A Constrained Random Simulation Tool In this section, we discuss a real-world tool, Simgen [YSP 99]. Simgen stands for simulation generation. It provides a constrained random simulation framework. Simgen is written in C++ and interfaces with a Verilog simulator through PLI. It recognizes a small set of syntax for defining constraints, randomization, and simulation control.

Randomization: There are two possible outcomes in solving the constraints: a. There is no solution, which we call an over-constraint. In simulation, this means not a single input is allowed at the current state. The current state is therefore called a dead-end state. Simulation has to be aborted upon reaching a dead-end state. b. There is at least one solution. One input is randomly picked, according to some user specified probability distribution. In this flow, constrained random generation is reduced to a generic constraint satisfaction problem of Boolean formulas.

In SVRC and SCV, additionally, randomization can be controlled by: 1) disabling and enabling randomization of certain variables or fields of variables, 2) changing the randomization seed, and 3) using the pre- and post-processing routines. 1. Constraint and randomization features of SVRC, SCV, and . 3 SystemVerilog Random Constraints In this section we cover the language constructs of SVRC. We begin with an overview of how constrained randomization takes place in a SystemVerilog High Level Verification Languages 43 environment.

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Constraint-Based Verification by Jun Yuan

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