Cambridge Computer Science Texts – serie

Simulating a continuous process on a (computer) model provides a means of understanding how a system will behave when it is subject to particular constraints. Computers are of particular use for this purpose as the system is one which involves differential equations, eg. the behaviour of the vehicle suspension systems and chemical reactions. The book describes how analogue, digital and hybrid computers are used in simulating continuous systems. Their use is illustrated in the text by a number of simple problems and most chapters also contain examples of varying complexity selected from a range of scientific and engineering disciplines. A short appendix describes the functioning of analogue and hybrid units; for the rest of the book a knowledge of electric circuit theory is not required.

This book is devoted to recursion in programming, the technique by which the solution to a problem is expressed partly in terms of the solution to a simpler version of the same problem. Ultimately the solution to the simplest version must be given explicitly. In functional programming, recursion has received its full due since it is quite often the only repetitive construct. However, the programming language used here is Pascal and the examples have been chosen accordingly. It makes an interesting contrast with the use of recursion in functional and logic programming. The early chapters consider simple linear recursion using examples such as finding the highest common factor of a pair of numbers, and processing linked lists. Subsequent chapters move up through binary recursion, with examples which include the Towers of Hanoi problem and symbolic differentiation, to general recursion. The book contains well over 100 examples.

Computing is an exact science and the systematic study of any aspect necessarily involves the use of mathematical models. Moreover, the rate at which the subject is evolving demands a facility for developing new mathematical systems to keep pace with new computing systems and this requires an appreciation of how mathematics works. An understanding of the underlying mathematical structure facilitates the construction of suitable computer programs to perform computations. Assuming no specific knowledge of mathematics, the authors describe all the basic concepts required and progress from sets (rather than numbers) through a variety of algebraic structures that permit the precise description, specification and subsequent analysis of many problems in computing. The material included provides the essential mathematical foundations for core topics of computer science and extends into the areas of language theory, abstract machine theory and computer geometry. Computer Mathematics will be of interest to undergraduate students of computer science and mathematics, post-graduate computing 'conversion' course students and computer professionals who need an introduction to the mathematics that underpins computer science theory.

Here is an introduction to functional programming and its associated systems. A unique feature is its use of the language Haskell for teaching both the rudiments and the finer points of the functional technique. Haskell is a new, internationally agreed and accepted functional language that is designed for teaching, research and applications, that has a complete formal description, that is freely available, and that is based on ideas that have a wide consensus. Thus it encapsulates some of the main thrusts of functional programming itself, which is a style of programming designed to confront the software crisis directly. Programs written in functional languages can be built up from smaller parts, and they can also be proved correct, important when software has to be reliable. Moreover, a certain amount of parallelism can be extracted from functional languages automatically. This book serves as an introduction both to functional programming and Haskell, and will be most useful to students, teachers and researchers in either of these areas. An especially valuable feature are the chapters on programming and implementation, along with a large number of exercises.

To perform computer simulation successfully, two rather different sets of skills are required. One of these relates to programming: a simulation program should do what its author intends and do it efficiently. The other is concerned with the collection and analysis of data: statistical tools have to be used in order to obtain with a minimum of effort, accurate and reliable estimates for the desired performance measures. Dr Mitrani covers both of these aspects of the simulation method. The important topics of point and interval estimation, simulation efficiency and the analysis of simulation experiments are discussed in detail. This book, first published in 1982, will be useful to both undergraduate and postgraduate students taking courses on simulation in departments of computer science, operations research and statistics in universities and polytechnics. It will be of benefit also to practitioners in the field.

By the time students have done some programming in one or two languages and have learnt the common ways of representing information in a computer, they will want to embark upon further study of theoretical or applied topics in computer science. Most will encounter problems that require for their solution one or more of the techniques described in this book: for example problems depending upon the formation and solution of different equations; the task of making lists of possible alternatives and of answering questions about them; or the search for discrete optima. Written by the same authors as the highly successful Information Representation and Manipulation in a Computer, this book describes algorithms of mathematical methods and illustrates their application with examples. The mathematical background needed is elementary algebra and calculus. Numerous exercises are provided, with hints to their solutions.

This 1987 book is a self-contained text on the probabilistic modelling method. It provides the reader with an understanding of the available results as well as with examples of their application. The only background assumed is a knowledge of basic calculus. The necessary fundamentals of probability are presented followed by an introduction to stochastic processes. The remainder of the book is devoted to the treatment of various single-station and their application to uni-programmed and multi-programmed systems and local and wide-area networks. Both exact and approximate solution methods are discussed, with as much emphasis on explaining the ideas and providing information, as on derivations and proofs. This book will still be of use for anyone with an interest in the history of computer science.

This textbook is an introduction to denotational semantics and its applications to programming languages. Dr Allison emphasizes a practical approach and the student is encouraged to write and test denotational definitions. The first section is devoted to the mathematical foundations of the subject and sufficient detail is given to illustrate the fundamental problems. The remainder of the book covers the use of denotational semantics to describe sequential programming languages such as Algol, Pascal and C. Throughout, numerous exercises, usually in Pascal, will help the student practise writing definitions and carry out simple applications. The book culminates in discussing an executable semantics of the logic-programming language Prolog. Being an introduction, advanced undergraduates in computer science and graduates new to the subject will find this a readily accessible account of one of the central topics of computer science.

This textbook is an introduction to the design and writing of computer programs. It leads the reader through all the stages of program construction from the original specifications through to the final program. The formal verification of intermediate versions of the program is studied in considerable detail. The authors show how, given the formal specification of a program, data structure and program structure diagrams are drawn and then converted into a procedural program in a program design language (PDL). They demonstrate the conversion of PDL into a variety of real programming languages including Pascal, FORTRAN, COBOL, and Assembler. The book also includes chapters on abstract data types, analysing existing programs, and a small case study. First-year undergraduates in computer science and graduates taking courses in computing will find this a comprehensive introduction to program construction.

This 1989 book provides an introduction to the immensely important area of computer networking. The book covers everything from systems linked by telephone lines to tightly coupled networks of processors using high speed links, and the correspondingly broad range of techniques that are needed. The emphasis throughout is on the understanding of the principles that may rapidly become out of date. However, detailed discussion of standards and systems is given where they are widely accepted and likely to be long-lasting. In particular the ARPANET and OSI standards are discussed. The author's style is extremely accessible, and many real-life examples are given to illustrate the discussion.

This textbook is designed as a first book on concurrent programming for computer science undergraduates, and provides a comprehensive introduction to the problems of concurrency. Concurrency is of vital importance in many areas of computer science, particularly in operating systems. It is also increasingly being taught in undergraduate courses. The book builds on the student's familiarity with sequential programming in a high level language, which will make it very accessible to computer science students. The book is concerned mainly with the high level aspects of concurrency, which will be equally applicable to traditional time sliced or more recent truly parallel systems.

Category theory has become increasingly important and popular in computer science, and many universities now have introductions to category theory as part of their courses for undergraduate computer scientists. The author is a respected category theorist and has based this textbook on a course given over the last few years at the University of Sydney. The theory is developed in a straightforward way, and is enriched with many examples from computer science. Thus this book meets the needs of undergradute computer scientists, and yet retains a level of mathematical correctness that will broaden its appeal to include students of mathematics new to category theory.

Category theory has become increasingly important and popular in computer science, and many universities now have introductions to category theory as part of their courses for undergraduate computer scientists. The author is a respected category theorist and has based this textbook on a course given over the last few years at the University of Sydney. The theory is developed in a straightforward way, and is enriched with many examples from computer science. Thus this book meets the needs of undergradute computer scientists, and yet retains a level of mathematical correctness that will broaden its appeal to include students of mathematics new to category theory.