Peter Sestoft

Neil D. Jones

Carsten K. Gomard

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.

Partial Evaluation and Automatic Program Generation

Dines Bjørner

Andreĭ Petrovich Ershov

The aim of Partial Evaluation and Mixed Computation is to construct, when given a program and some form of restriction on its usage (e.g. knowledge of some but not all of its input parameter values), a more efficient new or ''residual'' program that is equivalent to the original program when used according to the restriction. Compiling and compiler generation are just two of the many applications. It is thus a form of program transformation, but with more emphasis on purely automatic methods than traditional program transformation. This volume collects a variety of examples of current work in the field. The papers demonstrate the vitality of this emerging area with contributions covering many different aspects, such as programming languages, application areas, degrees of automation, degrees of formality, and technical methods.

Proceedings of the IFIP TC2 Workshop on Partial Evaluation and Mixed Computation, Gammel Avernæs, Denmark, 18-24 October, 1987

Partial Evaluation and Mixed Computation

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

From a Programming Perspective

Computability and Complexity

Markus Müller-Olm

The book constitutes the refereed proceedings of the 10th International Conference on Verification, Model Checking, and Abstract Interpretation, VMCAI 2009, held in Savannah, GA, USA, in January 2009 - co-located with POPL 2009, the 36th Annual Symposium on Principles of Programming Languages. The 24 revised full papers presented together with 3 invited talks and 2 invited tutorials were carefully reviewed and selected from 72 submissions. The papers address all current issues from the communities of verification, model checking, and abstract interpretation, facilitating interaction, cross-fertilization, and advancement of hybrid methods that combine the three areas.

Neil D. Jones

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