Alberto Sangiovanni-Vincentelli – författare

The Problem of the Unknown Component: Theory and Applications addresses the issue of designing a component that, combined with a known part of a system, conforms to an overall specification. The authors tackle this problem by solving abstract equations over a language. The most general solutions are studied when both synchronous and parallel composition operators are used. The abstract equations are specialized to languages associated with important classes of automata used for modeling systems. The book is a blend of theory and practice, which includes a description of a software package with applications to sequential synthesis of finite state machines. Specific topologies interconnecting the components, exact and heuristic techniques, and optimization scenarios are studied. Finally the scope is enlarged to domains like testing, supervisory control, game theory and synthesis for special omega languages. The authors present original results of the authors along with an overview of existing ones.

In electronic circuit and system design, the word noise is used to refer to any undesired excitation on the system. In other contexts, noise is also used to refer to signals or excitations which exhibit chaotic or random behavior. The source of noise can be either internal or external to the system. For instance, the thermal and shot noise generated within integrated circuit devices are in­ ternal noise sources, and the noise picked up from the environment through electromagnetic interference is an external one. Electromagnetic interference can also occur between different components of the same system. In integrated circuits (Ies), signals in one part of the system can propagate to the other parts of the same system through electromagnetic coupling, power supply lines and the Ie substrate. For instance, in a mixed-signal Ie, the switching activity in the digital parts of the circuit can adversely affect the performance of the analog section of the circuit by traveling through the power supply lines and the substrate. Prediction of the effect of these noise sources on the performance of an electronic system is called noise analysis or noise simulation. A methodology for the noise analysis or simulation of an electronic system usually has the following four components: 2 NOISE IN NONLINEAR ELECTRONIC CIRCUITS • Mathematical representations or models for the noise sources. • Mathematical model or representation for the system that is under the in­ fluence of the noise sources.

Analog circuit design is often the bottleneck when designing mixed analog-digital systems. A Top-Down, Constraint-Driven Design Methodology for Analog Integrated Circuits presents a new methodology based on a top-down, constraint-driven design paradigm that provides a solution to this problem. This methodology has two principal advantages: (1) it provides a high probability for the first silicon which meets all specifications, and (2) it shortens the design cycle. A Top-Down, Constraint-Driven Design Methodology for Analog Integrated Circuits is part of an ongoing research effort at the University of California at Berkeley in the Electrical Engineering and Computer Sciences Department. Many faculty and students, past and present, are working on this design methodology and its supporting tools. The principal goals are: (1) developing the design methodology, (2) developing and applying new tools, and (3) `proving' the methodology by undertaking `industrial strength' design examples. The work presented here is neither a beginning nor an end in the development of a complete top-down, constraint-driven design methodology, but rather a step in its development. This work is divided into three parts. Chapter 2 presents the design methodology along with foundation material. Chapters 3-8 describe supporting concepts for the methodology, from behavioral simulation and modeling to circuit module generators. Finally, Chapters 9-11 illustrate the methodology in detail by presenting the entire design cycle through three large-scale examples. These include the design of a current source D/A converter, a Sigma-Delta A/D converter, and a video driver system. Chapter 12 presents conclusions and current research topics. A Top-Down, Constraint-Driven Design Methodology for Analog Integrated Circuits will be of interest to analog and mixed-signal designers as well as CAD tool developers.

Synthesis of Finite State Machines: Functional Optimization is one of two monographs devoted to the synthesis of Finite State Machines (FSMs). This volume addresses functional optimization, whereas the second addresses logic optimization. By functional optimization here we mean the body of techniques that: compute all permissible sequential functions for a given topology of interconnected FSMs, and select a `best' sequential function out of the permissible ones. The result is a symbolic description of the FSM representing the chosen sequential function. By logic optimization here we mean the steps that convert a symbolic description of an FSM into a hardware implementation, with the goal to optimize objectives like area, testability, performance and so on. Synthesis of Finite State Machines: Functional Optimization is divided into three parts. The first part presents some preliminary definitions, theories and techniques related to the exploration of behaviors of FSMs. The second part presents an implicit algorithm for exact state minimization of incompletely specified finite state machines (ISFSMs), and an exhaustive presentation of explicit and implicit algorithms for the binate covering problem. The third part addresses the computation of permissible behaviors at a node of a network of FSMs and the related minimization problems of non-deterministic finite state machines (NDFSMs). Key themes running through the book are the exploration of behaviors contained in a non-deterministic FSM (NDFSM), and the representation of combinatorial problems arising in FSM synthesis by means of Binary Decision Diagrams (BDDs). Synthesis of Finite State Machines: Functional Optimization will be of interest to researchers and designers in logic synthesis, CAD and design automation.

Embedded systems are informally defined as a collection of programmable parts surrounded by ASICs and other standard components, that interact continuously with an environment through sensors and actuators. The programmable parts include micro-controllers and Digital Signal Processors (DSPs). Embedded systems are often used in life-critical situations, where reliability and safety are more important criteria than performance. Today, embedded systems are designed with an ad hoc approach that is heavily based on earlier experience with similar products and on manual design. Use of higher-level languages such as C helps structure the design somewhat, but with increasing complexity it is not sufficient. Formal verification and automatic synthesis of implementations are the surest ways to guarantee safety. Thus, the POLIS system which is a co-design environment for embedded systems is based on a formal model of computation. POLIS was initiated in 1988 as a research project at the University of California at Berkeley and, over the years, grew into a full design methodology with a software system supporting it. Hardware-Software Co-Design of Embedded Systems: The POLIS Approach is intended to give a complete overview of the POLIS system including its formal and algorithmic aspects. Hardware-Software Co-Design of Embedded Systems: The POLIS Approach will be of interest to embedded system designers (automotive electronics, consumer electronics and telecommunications), micro-controller designers, CAD developers and students.

Analog circuit design is often the bottleneck when designing mixed analog-digital systems. A Top-Down, Constraint-Driven Design Methodology for Analog Integrated Circuits presents a new methodology based on a top-down, constraint-driven design paradigm that provides a solution to this problem. This methodology has two principal advantages: (1) it provides a high probability for the first silicon which meets all specifications, and (2) it shortens the design cycle. A Top-Down, Constraint-Driven Design Methodology for Analog Integrated Circuits is part of an ongoing research effort at the University of California at Berkeley in the Electrical Engineering and Computer Sciences Department. Many faculty and students, past and present, are working on this design methodology and its supporting tools. The principal goals are: (1) developing the design methodology, (2) developing and applying new tools, and (3) `proving'' the methodology by undertaking `industrial strength'' design examples. The work presented here is neither a beginning nor an end in the development of a complete top-down, constraint-driven design methodology, but rather a step in its development. This work is divided into three parts. Chapter 2 presents the design methodology along with foundation material. Chapters 3-8 describe supporting concepts for the methodology, from behavioral simulation and modeling to circuit module generators. Finally, Chapters 9-11 illustrate the methodology in detail by presenting the entire design cycle through three large-scale examples. These include the design of a current source D/A converter, a Sigma-Delta A/D converter, and a video driver system. Chapter 12 presents conclusions and current research topics. A Top-Down, Constraint-Driven Design Methodology for Analog Integrated Circuits will be of interest to analog and mixed-signal designers as well as CAD tool developers.

Analog circuit design is often the bottleneck when designing mixed analog-digital systems. A Top-Down, Constraint-Driven Design Methodology for Analog Integrated Circuits presents a new methodology based on a top-down, constraint-driven design paradigm that provides a solution to this problem. This methodology has two principal advantages: (1) it provides a high probability for the first silicon which meets all specifications, and (2) it shortens the design cycle. A Top-Down, Constraint-Driven Design Methodology for Analog Integrated Circuits is part of an ongoing research effort at the University of California at Berkeley in the Electrical Engineering and Computer Sciences Department. Many faculty and students, past and present, are working on this design methodology and its supporting tools. The principal goals are: (1) developing the design methodology, (2) developing and applying new tools, and (3) `proving' the methodology by undertaking `industrial strength' design examples. The work presented here is neither a beginning nor an end in the development of a complete top-down, constraint-driven design methodology, but rather a step in its development. This work is divided into three parts. Chapter 2 presents the design methodology along with foundation material. Chapters 3-8 describe supporting concepts for the methodology, from behavioral simulation and modeling to circuit module generators. Finally, Chapters 9-11 illustrate the methodology in detail by presenting the entire design cycle through three large-scale examples. These include the design of a current source D/A converter, a Sigma-Delta A/D converter, and a video driver system. Chapter 12 presents conclusions and current research topics. A Top-Down, Constraint-Driven Design Methodology for Analog Integrated Circuits will be of interest to analog and mixed-signal designers as well as CAD tool developers.

In electronic circuit and system design, the word noise is used to refer to any undesired excitation on the system. In other contexts, noise is also used to refer to signals or excitations which exhibit chaotic or random behavior. The source of noise can be either internal or external to the system. For instance, the thermal and shot noise generated within integrated circuit devices are in­ ternal noise sources, and the noise picked up from the environment through electromagnetic interference is an external one. Electromagnetic interference can also occur between different components of the same system. In integrated circuits (Ies), signals in one part of the system can propagate to the other parts of the same system through electromagnetic coupling, power supply lines and the Ie substrate. For instance, in a mixed-signal Ie, the switching activity in the digital parts of the circuit can adversely affect the performance of the analog section of the circuit by traveling through the power supply lines and the substrate. Prediction of the effect of these noise sources on the performance of an electronic system is called noise analysis or noise simulation. A methodology for the noise analysis or simulation of an electronic system usually has the following four components: 2 NOISE IN NONLINEAR ELECTRONIC CIRCUITS • Mathematical representations or models for the noise sources. • Mathematical model or representation for the system that is under the in­ fluence of the noise sources.

Embedded systems are informally defined as a collection of programmable parts surrounded by ASICs and other standard components, that interact continuously with an environment through sensors and actuators. The programmable parts include micro-controllers and Digital Signal Processors (DSPs). Embedded systems are often used in life-critical situations, where reliability and safety are more important criteria than performance. Today, embedded systems are designed with an ad hoc approach that is heavily based on earlier experience with similar products and on manual design. Use of higher-level languages such as C helps structure the design somewhat, but with increasing complexity it is not sufficient. Formal verification and automatic synthesis of implementations are the surest ways to guarantee safety. Thus, the POLIS system which is a co-design environment for embedded systems is based on a formal model of computation. POLIS was initiated in 1988 as a research project at the University of California at Berkeley and, over the years, grew into a full design methodology with a software system supporting it. Hardware-Software Co-Design of Embedded Systems: The POLIS Approach is intended to give a complete overview of the POLIS system including its formal and algorithmic aspects. Hardware-Software Co-Design of Embedded Systems: The POLIS Approach will be of interest to embedded system designers (automotive electronics, consumer electronics and telecommunications), micro-controller designers, CAD developers and students.

Embedded Systems design becomes more complex as increasingly sophisticated functionality is added to designs. In addition to considerations of cost, performance, and time-to-market, various system integration issues become challenging, given the inherently heterogeneous nature of embedded systems. Platform Based Design introduces a rigorous design methodology to address the various challenges posed by complex, heterogeneous, embedded systems.

This book offers readers broad coverage of techniques to model, verify and validate the behavior and performance of complex distributed embedded systems.  The authors attempt to bridge the gap between the three disciplines of model-based design, real-time analysis and model-driven development, for a better understanding of the ways in which new development flows can be constructed, going from system-level modeling to the correct and predictable generation of a distributed implementation, leveraging current and future research results.

This book offers readers broad coverage of techniques to model, verify and validate the behavior and performance of complex distributed embedded systems.  The authors attempt to bridge the gap between the three disciplines of model-based design, real-time analysis and model-driven development, for a better understanding of the ways in which new development flows can be constructed, going from system-level modeling to the correct and predictable generation of a distributed implementation, leveraging current and future research results.

In electronic circuit and system design, the word noise is used to refer to any undesired excitation on the system. In other contexts, noise is also used to refer to signals or excitations which exhibit chaotic or random behavior. The source of noise can be either internal or external to the system. For instance, the thermal and shot noise generated within integrated circuit devices are in­ ternal noise sources, and the noise picked up from the environment through electromagnetic interference is an external one. Electromagnetic interference can also occur between different components of the same system. In integrated circuits (Ies), signals in one part of the system can propagate to the other parts of the same system through electromagnetic coupling, power supply lines and the Ie substrate. For instance, in a mixed-signal Ie, the switching activity in the digital parts of the circuit can adversely affect the performance of the analog section of the circuit by traveling through the power supply lines and the substrate. Prediction of the effect of these noise sources on the performance of an electronic system is called noise analysis or noise simulation. A methodology for the noise analysis or simulation of an electronic system usually has the following four components: 2 NOISE IN NONLINEAR ELECTRONIC CIRCUITS • Mathematical representations or models for the noise sources. • Mathematical model or representation for the system that is under the in­ fluence of the noise sources.

Embedded systems are informally defined as a collection of programmable parts surrounded by ASICs and other standard components, that interact continuously with an environment through sensors and actuators. The programmable parts include micro-controllers and Digital Signal Processors (DSPs). Embedded systems are often used in life-critical situations, where reliability and safety are more important criteria than performance. Today, embedded systems are designed with an ad hoc approach that is heavily based on earlier experience with similar products and on manual design. Use of higher-level languages such as C helps structure the design somewhat, but with increasing complexity it is not sufficient. Formal verification and automatic synthesis of implementations are the surest ways to guarantee safety. Thus, the POLIS system which is a co-design environment for embedded systems is based on a formal model of computation. POLIS was initiated in 1988 as a research project at the University of California at Berkeley and, over the years, grew into a full design methodology with a software system supporting it. Hardware-Software Co-Design of Embedded Systems: The POLIS Approach is intended to give a complete overview of the POLIS system including its formal and algorithmic aspects. Hardware-Software Co-Design of Embedded Systems: The POLIS Approach will be of interest to embedded system designers (automotive electronics, consumer electronics and telecommunications), micro-controller designers, CAD developers and students.

The Problem of the Unknown Component: Theory and Applications addresses the issue of designing a component that, combined with a known part of a system, conforms to an overall specification. The authors tackle this problem by solving abstract equations over a language. The most general solutions are studied when both synchronous and parallel composition operators are used. The abstract equations are specialized to languages associated with important classes of automata used for modeling systems. The book is a blend of theory and practice, which includes a description of a software package with applications to sequential synthesis of finite state machines. Specific topologies interconnecting the components, exact and heuristic techniques, and optimization scenarios are studied. Finally the scope is enlarged to domains like testing, supervisory control, game theory and synthesis for special omega languages. The authors present original results of the authors along with an overview of existing ones.

This book offers readers broad coverage of techniques to model, verify and validate the behavior and performance of complex distributed embedded systems.  The authors attempt to bridge the gap between the three disciplines of model-based design, real-time analysis and model-driven development, for a better understanding of the ways in which new development flows can be constructed, going from system-level modeling to the correct and predictable generation of a distributed implementation, leveraging current and future research results.

Addressing the rising security issues during the design stages of cyber-physical systems, this book develops a systematic approach to address security at early design stages together with all other design constraints. Cyber-attacks become more threatening as systems are becoming more connected with the surrounding environment, infrastructures, and other systems. Security mechanisms can be designed to protect against attacks and meet security requirements, but there are many challenges of applying security mechanisms to cyber-physical systems including open environments, limited resources, strict timing requirements, and large number of devices. Designed for researchers and professionals, this book is valuable for individuals working in network systems, security mechanisms, and system design. It is also suitable for advanced-level students of computer science.

Addressing the rising security issues during the design stages of cyber-physical systems, this book develops a systematic approach to address security at early design stages together with all other design constraints. Cyber-attacks become more threatening as systems are becoming more connected with the surrounding environment, infrastructures, and other systems. Security mechanisms can be designed to protect against attacks and meet security requirements, but there are many challenges of applying security mechanisms to cyber-physical systems including open environments, limited resources, strict timing requirements, and large number of devices. Designed for researchers and professionals, this book is valuable for individuals working in network systems, security mechanisms, and system design. It is also suitable for advanced-level students of computer science. 

Addressing the rising security issues during the design stages of cyber-physical systems, this book develops a systematic approach to address security at early design stages together with all other design constraints. Cyber-attacks become more threatening as systems are becoming more connected with the surrounding environment, infrastructures, and other systems. Security mechanisms can be designed to protect against attacks and meet security requirements, but there are many challenges of applying security mechanisms to cyber-physical systems including open environments, limited resources, strict timing requirements, and large number of devices. Designed for researchers and professionals, this book is valuable for individuals working in network systems, security mechanisms, and system design. It is also suitable for advanced-level students of computer science.

The purpose of the EMSOFT Workshop, inaugurated last year at Lake Tahoe, is to bring together researchers and practitioners interested in the foundations and methods of embedded software design with the goal of improving subst- tially the state of the art and stimulating the debate between researchers and designers. The scope of the EMSOFT Workshop spans all aspects of embedded software, including operating systems and middleware, programming languages and compilers, modeling and validation, software engineering and programming methodologies, scheduling and execution-time analysis, formal methods, c- munication protocols and fault tolerance. While the ?rst Workshop included only invited papers because of the need to establish a common framework and a basis for the scienti?c contributions, for this second EMSOFT, we attempted to strike a balance between invited and selected contributions. The program included 17 selected and 13 invited c- tributions.The invited speakers were: Giorgio Buttazzo (University of Pavia), PaoloFaraboschi(Hewlett-PackardLaboratories),NicolasHalbwachs(Verimag), DavidHarel(WeizmannInstitute),ChristophKirsch(UniversityofCaliforniaat Berkeley), Luciano Lavagno (Politecnico di Torino and Cadence Research Labs), Nancy Leveson (MIT), Sharad Malik (Princeton), Al Mok (University of Texas at Austin), Amir Pnueli (Weizmann Institute), Lui Sha (University of Illinois at Urbana-Champaign), Douglas Schmidt (University of California at Irvine), and Bran Selic (Rational).