Petri Nets were introduced and still successfully used to analyze and model discrete event systems especially in engineering and computer sciences such as in automatic control.

Recently this discrete Petri Nets formalism was successfully extended to continuous and hybrid systems. This monograph presents a well written and clearly organized introduction in the standard methods of Petri Nets with the aim to reach an accurate understanding of continuous and hybrid Petri Nets, while preserving the consistency of basic concepts throughout the book. The book is a monograph as well as a didactic tool which is easy to understand due to many simple solved examples and detailed figures. In its second completely reworked edition various sections, concepts and recently developed algorithms are added as well as additional examples/exercises.

This well-organized reference/text introduces a theory of random testing in digital circuits for the first time and offers practical guidance for the implementation of random pattern generators, signature analyzers, design for random testability, and testing results. Contains several new and unpublished results The fruit of two decades' research by the author, Random Testing of Digital Circuits calculates random test lengths for combinational and sequential circuits, memory circuits, and microprocessors provides experimental results derived from real circuits, not simulations illustrates the efficiency of random testing for nontarget faults explores performance measurements and design for random pattern testing profiles both single and multiple input signature analyzers describes testing procedures for complex sequential machines examines results from TTL circuits, LSI CMOS circuits, and the Motorola 6800 microprocessor highlights both software and hardware generation of random test sequences and more Random Testing of Digital Circuits serves as an excellent reference for electrical and electronics, circuit test, circuit design, communications, component, and control engineers; applied mathematicians and statisticians; computer scientists; and an outstanding text for upper-level undergraduate and graduate students in these disciplines.