Partial evaluation reconciles generality with efficiency by providing automatic specialization and optimization of programs. This book covers the entire field of partial evaluation; provides simple and complete algorithms; and demonstrates that specialization can increase efficiency.

Program generation holds the promise of helping to bridge the gap between application-level problem solutions and efficient implementations at the level of today's source programs as written in C or Java. Thus, program generation can substantially contribute to reducing production cost and time-to-market in future software production, while improving the quality and stability of the product. This book is about domain-specific program generation; it is the outcome of a Dagstuhl seminar on the topic held in March 2003. After an introductory preface by the volume editors, the 18 carefully reviewed revised full papers presented are organized into topical sections on - surveys of domain-specific programming technologies - domain-specific programming languages - tool support for program generation - domain-specific techniques for program optimization

As the complexity of software increases, researchers and practicioners continue to seek better techniques for engineering the construction of evolution of software. Partial evaluation is an attractive technology for modern software construction since it provides automatic tools for software specialization and is based on rigorous semantic foundations. This book is based on a school held at DIKU Copenhagen, Denmark in summer 1998 during which leading researchers summarized the state of the art in partial evaluation. The lectures presented survey the foundations of partial evaluation in a clear and rigorous manner and practically introduce several existing partial evaluators with numerous examples. The second part of the book is devoted to more sophisticated theoretical aspects, advances systems and applications, and highlights open problems and challenges. The book is ideally suited for advanced courses and for self study.

This book uses a functional programming language (F#) as a metalanguage to present all concepts and examples, and thus has an operational flavour, enabling practical experiments and exercises. It includes basic concepts such as abstract syntax, interpretation, stack machines, compilation, type checking, garbage collection, and real machine code. Also included are more advanced topics on polymorphic types, type inference using unification, co- and contravariant types, continuations, and backwards code generation with on-the-fly peephole optimization. This second edition includes two new chapters. One describes compilation and type checking of a full functional language, tying together the previous chapters. The other describes how to compile a C subset to real (x86) hardware, as a smooth extension of the previously presented compilers.The examples present several interpreters and compilers for toy languages, including compilers for a small but usable subset of C, abstract machines, a garbage collector, and ML-style polymorphic type inference. Each chapter has exercises. Programming Language Concepts covers practical construction of lexers and parsers, but not regular expressions, automata and grammars, which are well covered already. It discusses the design and technology of Java and C# to strengthen students’ understanding of these widely used languages.

This book collects very recent results on theoretical and observational astronomy. The main topics are the study of stellar populations of the Milky Way and of other spiral galaxies in the near infrared, the IR observations of local group galaxies and disk galaxies, and the dynamic structure of spiral galaxies. The final sections treat dust structures and nuclear activity in galaxies.

This book is a tutorial written by researchers and developers behind the FEniCS Project and explores an advanced, expressive approach to the development of mathematical software. The presentation spans mathematical background, software design and the use of FEniCS in applications. Theoretical aspects are complemented with computer code which is available as free/open source software. The book begins with a special introductory tutorial for beginners. Following are chapters in Part I addressing fundamental aspects of the approach to automating the creation of finite element solvers. Chapters in Part II address the design and implementation of the FEnicS software. Chapters in Part III present the application of FEniCS to a wide range of applications, including fluid flow, solid mechanics, electromagnetics and geophysics.

This book constitutes the refereed proceedings of the Second Symposium on Programs as Data Objects, PADO 2001, held in Aarhus, Denmark, in May 2001. The 14 revised full papers presented were carefully reviewed and selected from 30 submissions. Various aspects of looking at programs as data objects are covered from the point of view of program analysis, program transformation, computational complexity, etc.

Computability and complexity theory should be of central concern to practitioners as well as theorists. Unfortunately, however, the field is known for its impenetrability. Neil Jones's goal as an educator and author is to build a bridge between computability and complexity theory and other areas of computer science, especially programming. In a shift away from the Turing machine- and G�del number-oriented classical approaches, Jones uses concepts familiar from programming languages to make computability and complexity more accessible to computer scientists and more applicable to practical programming problems. According to Jones, the fields of computability and complexity theory, as well as programming languages and semantics, have a great deal to offer each other. Computability and complexity theory have a breadth, depth, and generality not often seen in programming languages. The programming language community, meanwhile, has a firm grasp of algorithm design, presentation, and implementation. In addition, programming languages sometimes provide computational models that are more realistic in certain crucial aspects than traditional models. New results in the book include a proof that constant time factors do matter for its programming-oriented model of computation. (In contrast, Turing machines have a counterintuitive "constant speedup" property: that almost any program can be made to run faster, by any amount. Its proof involves techniques irrelevant to practice.) Further results include simple characterizations in programming terms of the central complexity classes PTIME and LOGSPACE, and a new approach to complete problems for NLOGSPACE, PTIME, NPTIME, and PSPACE, uniformly based on Boolean programs. Foundations of Computing series

Program synthesis is the task of automatically finding a program in the underlying programming language that satisfies the user intent expressed in the form of some specification. Since the inception of artificial intelligence in the 1950s, this problem has been considered the holy grail of Computer Science. Despite inherent challenges in the problem such as ambiguity of user intent and a typically enormous search space of programs, the field of program synthesis has developed many different techniques that enable program synthesis in different real-life application domains. It is now used successfully in software engineering, biological discovery, compute-raided education, end-user programming, and data cleaning. In the last decade, several applications of synthesis in the field of programming by examples have been deployed in mass-market industrial products. This monograph is a general overview of the state-of-the-art approaches to program synthesis, its applications, and subfields. It discusses the general principles common to all modern synthesis approaches such as syntactic bias, oracle-guided inductive search, and optimization techniques. We then present a literature review covering the four most common state-of-the-art techniques in program synthesis: enumerative search, constraint solving, stochastic search, and deduction-based programming by examples. It concludes with a brief list of future horizons for the field.

This book presents the most up-to-date coverage of procedural content generation (PCG) for games, specifically the procedural generation of levels, landscapes, items, rules, quests, or other types of content. Each chapter explains an algorithm type or domain, including fractal methods, grammar-based methods, search-based and evolutionary methods, constraint-based methods, and narrative, terrain, and dungeon generation. The authors are active academic researchers and game developers, and the book is appropriate for undergraduate and graduate students of courses on games and creativity; game developers who want to learn new methods for content generation; and researchers in related areas of artificial intelligence and computational intelligence.