Concurrent constraint programming (ccp) is a recent development in programming language design. Its central contribution is the notion of partial information provided by a shared constraint store. This constraint store serves as a communication medium between concurrent threads of control and as a vehicle for their synchronization. Objects for Concurrent Constraint Programming analyzes the possibility of supporting object-oriented programming in ccp. Starting from established approaches, the book covers various object models and discusses their properties. Small Oz, a sublanguage of the ccp language Oz, is used as a model language for this analysis. This book presents a general-purpose object system for Small Oz and describes its implementation and expressivity for concurrent computation. Objects for Concurrent Constraint Programming is written for programming language researchers with an interest in programming language aspects of concurrency, object-oriented programming, or constraint programming. Programming language implementors will benefit from the rigorous treatment of the efficient implementation of Small Oz. Oz programmers will get a first-hand view of the design decisions that lie behind the Oz object system.

Constraint Programming is an approach for modeling and solving combi- torial problems that has proven successful in many applications. It builds on techniques developed in Arti?cial Intelligence, Logic Programming, and - erations Research. Key techniques are constraint propagation and heuristic search. Constraint Programming is based on an abstraction that decomposes a problem solver into a reusable constraint engine and a declarative program modeling the problem. The constraint engine implements the required pr- agation and search algorithms. It can be realized as a library for a general purpose programming language (e.g. C++), as an extension of an existing language (e.g. Prolog), or as a system with its own dedicated language. The present book is concerned with the architecture and implementation of constraint engines. It presents a new, concurrent architecture that is far superior to the sequential architecture underlying Prolog. The new archit- ture is based on concurrent search with copying and recomputation rather than sequential search with trailing and backtracking. One advantage of the concurrent approach is that it accommodates any search strategy. Furth- more, it considerably simpli?es the implementation of constraint propagation algorithms since it eliminates the need to account for trailing and backtra- ing. The book investigates an expressive generalization of the concurrent - chitecture that accommodates propagation-preserving combinators (known as deep guard combinators) for negation, disjunction, implication, and re- cation of constraint propagators. Such combinators are beyond the scope of Prolog’s technology. In the concurrent approach they can be obtained with a re?ective encapsulation primitive.

This book describes the benefits that emerge when the fields of constraint programming and concurrency meet. On the one hand, constraints can be used in concurrency theory to increase the conciseness and the expressive power of concurrent languages from a pragmatic point of view. On the other hand, problems modeled by using constraints can be solved faster and more efficiently using a concurrent system. Both directions are explored providing two separate lines of development. Firstly the expressive power of a concurrent language is studied, namely Constraint Handling Rules, that supports constraints as a primitive construct. The features of this language which make it Turing powerful are shown. Then a framework is proposed to solve constraint problems that is intended to be deployed on a concurrent system. For the development of this framework the concurrent language Jolie following the Service Oriented paradigm is used. Based on this experience, an extension to Service Oriented Languages is also proposed in order to overcome some of their limitations and to improve the development of concurrent applications.

Constraint programming aims at supporting a wide range of complex applications, which are often modeled naturally in terms of constraints. Early work, in the 1960s and 1970s, made use of constraints in computer graphics, user interfaces, and artificial intelligence. Such work introduced a declarative component in otherwise-procedural systems to reduce the development effort.

Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, computer science, databases, programming languages, and operations research. Constraint programming is currently applied with success to many domains, such as scheduling, planning, vehicle routing, configuration, networks, and bioinformatics.The aim of this handbook is to capture the full breadth and depth of the constraint programming field and to be encyclopedic in its scope and coverage. While there are several excellent books on constraint programming, such books necessarily focus on the main notions and techniques and cannot cover also extensions, applications, and languages. The handbook gives a reasonably complete coverage of all these lines of work, based on constraint programming, so that a reader can have a rather precise idea of the whole field and its potential. Of course each line of work is dealt with in a survey-like style, where some details may be neglected in favor of coverage. However, the extensive bibliography of each chapter will help the interested readers to find suitable sources for the missing details. Each chapter of the handbook is intended to be a self-contained survey of a topic, and is written by one or more authors who are leading researchers in the area.The intended audience of the handbook is researchers, graduate students, higher-year undergraduates and practitioners who wish to learn about the state-of-the-art in constraint programming. No prior knowledge about the field is necessary to be able to read the chapters and gather useful knowledge. Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas.The handbook is organized in two parts. The first part covers the basic foundations of constraint programming, including the history, the notion of constraint propagation, basic search methods, global constraints, tractability and computational complexity, and important issues in modeling a problem as a constraint problem. The second part covers constraint languages and solver, several useful extensions to the basic framework (such as interval constraints, structured domains, and distributed CSPs), and successful application areas for constraint programming. - Covers the whole field of constraint programming- Survey-style chapters- Five chapters on applications

Teaching the science and the technology of programming as a unified discipline that shows the deep relationships between programming paradigms. This innovative text presents computer programming as a unified discipline in a way that is both practical and scientifically sound. The book focuses on techniques of lasting value and explains them precisely in terms of a simple abstract machine. The book presents all major programming paradigms in a uniform framework that shows their deep relationships and how and where to use them together. After an introduction to programming concepts, the book presents both well-known and lesser-known computation models ("programming paradigms"). Each model has its own set of techniques and each is included on the basis of its usefulness in practice. The general models include declarative programming, declarative concurrency, message-passing concurrency, explicit state, object-oriented programming, shared-state concurrency, and relational programming. Specialized models include graphical user interface programming, distributed programming, and constraint programming. Each model is based on its kernel language—a simple core language that consists of a small number of programmer-significant elements. The kernel languages are introduced progressively, adding concepts one by one, thus showing the deep relationships between different models. The kernel languages are defined precisely in terms of a simple abstract machine. Because a wide variety of languages and programming paradigms can be modeled by a small set of closely related kernel languages, this approach allows programmer and student to grasp the underlying unity of programming. The book has many program fragments and exercises, all of which can be run on the Mozart Programming System, an Open Source software package that features an interactive incremental development environment.