A Practical Theory Of Programming

There are several theories of programming. The first usable theory, often called "Hoare's Logic", is still probably the most widely known. In it, a specification is a pair of predicates: a precondition and postcondition (these and all technical terms will be defined in due course). Another popular and closely related theory by Dijkstra uses the weakest precondition predicate transformer, which is a function from programs and postconditions to preconditions. lones's Vienna Development Method has been used to advantage in some industries; in it, a specification is a pair of predicates (as in Hoare's Logic), but the second predicate is a relation. Temporal Logic is yet another formalism that introduces some special operators and quantifiers to describe some aspects of computation. The theory in this book is simpler than any of those just mentioned. In it, a specification is just a boolean expression. Refinement is just ordinary implication. This theory is also more general than those just mentioned, applying to both terminating and nonterminating computation, to both sequential and parallel computation, to both stand-alone and interactive computation. And it includes time bounds, both for algorithm classification and for tightly constrained real-time applications.

This book unifies a broad range of programming language concepts under the framework of type systems and structural operational semantics.

Distributed Programming: Theory and Practice presents a practical and rigorous method to develop distributed programs that correctly implement their specifications. The method also covers how to write specifications and how to use them. Numerous examples such as bounded buffers, distributed locks, message-passing services, and distributed termination detection illustrate the method. Larger examples include data transfer protocols, distributed shared memory, and TCP network sockets. Distributed Programming: Theory and Practice bridges the gap between books that focus on specific concurrent programming languages and books that focus on distributed algorithms. Programs are written in a "real-life" programming notation, along the lines of Java and Python with explicit instantiation of threads and programs. Students and programmers will see these as programs and not "merely" algorithms in pseudo-code. The programs implement interesting algorithms and solve problems that are large enough to serve as projects in programming classes and software engineering classes. Exercises and examples are included at the end of each chapter with on-line access to the solutions. Distributed Programming: Theory and Practice is designed as an advanced-level text book for students in computer science and electrical engineering. Programmers, software engineers and researchers working in this field will also find this book useful.

Drawing Programs: The Theory and Practice of Schematic Functional Programming describes a diagrammatic (schematic) approach to programming. It introduces a sophisticated tool for programmers who would rather work with diagrams than with text. The language is a complete functional language that has evolved into a representation scheme that is unique. The result is a simple coherent description of the process of modelling with the computer. The experience of using this tool is introduced gradually with examples, small projects and exercises. The new computational theory behind the tool is interspersed between these practical descriptions so that the reasons for the activity can be understood and the activity, in turn, illustrates some elements of the theory Access to the tool, its source code and a set of examples that range from the simple to the complex is free (see www.springer.com/978-1-84882-617-5). A description of the tool’s construction and how it may be extended is also given. The authors’ experience with undergraduates and graduates who have the understanding and skill of a functional language learnt through using schema have also shown an enhanced ability to program in other computer languages. Readers are provided with a set of concepts that will ensure a good robust program design and, what is more important, a path to error free programming.

Elements of Programming provides a different understanding of programming than is presented elsewhere. Its major premise is that practical programming, like other areas of science and engineering, must be based on a solid mathematical foundation. The book shows that algorithms implemented in a real programming language, such as C++, can operate in the most general mathematical setting. For example, the fast exponentiation algorithm is defined to work with any associative operation. Using abstract algorithms leads to efficient, reliable, secure, and economical software.

Precision programming. Elements of logical expression. Elements of program expression. Structured programs. Reading structured programs. The correctness of structured programs. Writing structured programs.

An accessible and rigorous textbook for introducing undergraduates to computer science theory What Can Be Computed? is a uniquely accessible yet rigorous introduction to the most profound ideas at the heart of computer science. Crafted specifically for undergraduates who are studying the subject for the first time, and requiring minimal prerequisites, the book focuses on the essential fundamentals of computer science theory and features a practical approach that uses real computer programs (Python and Java) and encourages active experimentation. It is also ideal for self-study and reference. The book covers the standard topics in the theory of computation, including Turing machines and finite automata, universal computation, nondeterminism, Turing and Karp reductions, undecidability, time-complexity classes such as P and NP, and NP-completeness, including the Cook-Levin Theorem. But the book also provides a broader view of computer science and its historical development, with discussions of Turing's original 1936 computing machines, the connections between undecidability and Gödel's incompleteness theorem, and Karp's famous set of twenty-one NP-complete problems. Throughout, the book recasts traditional computer science concepts by considering how computer programs are used to solve real problems. Standard theorems are stated and proven with full mathematical rigor, but motivation and understanding are enhanced by considering concrete implementations. The book's examples and other content allow readers to view demonstrations of—and to experiment with—a wide selection of the topics it covers. The result is an ideal text for an introduction to the theory of computation. An accessible and rigorous introduction to the essential fundamentals of computer science theory, written specifically for undergraduates taking introduction to the theory of computation Features a practical, interactive approach using real computer programs (Python in the text, with forthcoming Java alternatives online) to enhance motivation and understanding Gives equal emphasis to computability and complexity Includes special topics that demonstrate the profound nature of key ideas in the theory of computation Lecture slides and Python programs are available at whatcanbecomputed.com

Anyone who develops software for a living needs a proven way to produce it better, faster, and cheaper. The Productive Programmer offers critical timesaving and productivity tools that you can adopt right away, no matter what platform you use. Master developer Neal Ford not only offers advice on the mechanics of productivity-how to work smarter, spurn interruptions, get the most out your computer, and avoid repetition-he also details valuable practices that will help you elude common traps, improve your code, and become more valuable to your team. You'll learn to: Write the test before you write the code Manage the lifecycle of your objects fastidiously Build only what you need now, not what you might need later Apply ancient philosophies to software development Question authority, rather than blindly adhere to standards Make hard things easier and impossible things possible through meta-programming Be sure all code within a method is at the same level of abstraction Pick the right editor and assemble the best tools for the job This isn't theory, but the fruits of Ford's real-world experience as an Application Architect at the global IT consultancy ThoughtWorks. Whether you're a beginner or a pro with years of experience, you'll improve your work and your career with the simple and straightforward principles in The Productive Programmer.

A comprehensive introduction to type systems and programming languages. A type system is a syntactic method for automatically checking the absence of certain erroneous behaviors by classifying program phrases according to the kinds of values they compute. The study of type systems—and of programming languages from a type-theoretic perspective—has important applications in software engineering, language design, high-performance compilers, and security. This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages. The approach is pragmatic and operational; each new concept is motivated by programming examples and the more theoretical sections are driven by the needs of implementations. Each chapter is accompanied by numerous exercises and solutions, as well as a running implementation, available via the Web. Dependencies between chapters are explicitly identified, allowing readers to choose a variety of paths through the material. The core topics include the untyped lambda-calculus, simple type systems, type reconstruction, universal and existential polymorphism, subtyping, bounded quantification, recursive types, kinds, and type operators. Extended case studies develop a variety of approaches to modeling the features of object-oriented languages.