The Formal Semantics of Programming Languages provides the basic mathematical techniques necessary for those who are beginning a study of the semantics and logics of programming languages. These techniques will allow students to invent, formalize, and justify rules with which to reason about a variety of programming languages. Although the treatment is elementary, several of the topics covered are drawn from recent research, including the vital area of concurency. The book contains many exercises ranging from simple to miniprojects.Starting with basic set theory, structural operational semantics is introduced as a way to define the meaning of programming languages along with associated proof techniques. Denotational and axiomatic semantics are illustrated on a simple language of while-programs, and fall proofs are given of the equivalence of the operational and denotational semantics and soundness and relative completeness of the axiomatic semantics. A proof of Godel's incompleteness theorem, which emphasizes the impossibility of achieving a fully complete axiomatic semantics, is included. It is supported by an appendix providing an introduction to the theory of computability based on while-programs. Following a presentation of domain theory, the semantics and methods of proof for several functional languages are treated. The simplest language is that of recursion equations with both call-by-value and call-by-name evaluation. This work is extended to lan guages with higher and recursive types, including a treatment of the eager and lazy lambda-calculi. Throughout, the relationship between denotational and operational semantics is stressed, and the proofs of the correspondence between the operation and denotational semantics are provided. The treatment of recursive types - one of the more advanced parts of the book - relies on the use of information systems to represent domains. The book concludes with a chapter on parallel programming languages, accompanied by a discussion of methods for specifying and verifying nondeterministic and parallel programs.

An approach to software design that introduces a fully automated analysis giving designers immediate feedback, now featuring the latest version of the Alloy language. In Software Abstractions Daniel Jackson introduces an approach to software design that draws on traditional formal methods but exploits automated tools to find flaws as early as possible. This approach—which Jackson calls “lightweight formal methods” or “agile modeling”—takes from formal specification the idea of a precise and expressive notation based on a tiny core of simple and robust concepts but replaces conventional analysis based on theorem proving with a fully automated analysis that gives designers immediate feedback. Jackson has developed Alloy, a language that captures the essence of software abstractions simply and succinctly, using a minimal toolkit of mathematical notions. This revised edition updates the text, examples, and appendixes to be fully compatible with Alloy 4.

This book contains enough mnaterial for three complete courses of study. It provides an introduction to the world of logic, sets and relations. It explains the use of the Znotation in the specification of realistic systems. It shows how Z specifications may be refined to produce executable code; this is demonstrated in a selection of case studies. The essentials of specification, refinement and proof are covered, revealing techniques never previously published. Exercises, Solutions and set of Tranparencies are available via http://www.comlab.ox.ac.uk/usingz.html

This tutorial for graduate students covers practical and theoretical aspects of separation logic with constructions and proofs in Coq.

Ontological modelling today is applied in many areas of science and technology, including the Semantic Web. The W3C standard OWL defines one of the most important ontology languages based on the semantics of description logics. An alternative is to use rule languages in knowledge modelling, as proposed in the W3C’s RIF standard. So far, it has often been unclear how to combine both technologies without sacrificing essential computational properties. This book explains this problem and presents new solutions that have recently been proposed. Extensive introductory chapters provide the necessary background for understanding the goals and challenges of this field, whereas advanced chapters discuss novel solutions in full detail. Enriched knowledge representation languages that are introduced include DL Rules, Horn description logics, and DL+safe Rules. In each of these cases, emphasis is put on finding a favourable trade-off between expressiveness and computational complexity. This naturally leads to the light-weight DL rule language ELP which illustrates that expressive ontological modelling and tractable inferencing can indeed go together. Comprehensive references for further reading are provided throughout the book.

This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, security, and approximate computing. Comprehensive survey chapters make the material accessible to graduate students and non-experts. This title is also available as Open Access on Cambridge Core.

Providing a thorough treatment of most elementary program development techniques, this revised edition covers topics such as procedures, parameters, recursion and data refinement, with the integration of specification, development and coding, based on ordinary (classical) logic.