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A student introduction to the design of algorithms for problem solving. Written from a functional programming perspective, the text should appeal to anyone studying algorithms. Included are end-of-chapter exercises and bibliographic references.
This book presents a variety of widely used algorithms, expressing them in a pure functional programming language to make their structure and operation clearer to readers. In the opening chapter the author introduces the specific notations that constitute the variant of Scheme that he uses. The second chapter introduces many of the simpler and more general patterns available in functional programming. The chapters that follow introduce and explain data structures, sorting, combinatorial constructions, graphs, and sublist search. Throughout the book the author presents the algorithms in a purely functional version of the Scheme programming language, which he makes available on his website. The book is supported with exercises, and it is suitable for undergraduate and graduate courses on programming techniques.
This book presents a variety of widely used algorithms, expressing them in a pure functional programming language to make their structure and operation clearer to readers. In the opening chapter the author introduces the specific notations that constitute the variant of Scheme that he uses. The second chapter introduces many of the simpler and more general patterns available in functional programming. The chapters that follow introduce and explain data structures, sorting, combinatorial constructions, graphs, and sublist search. Throughout the book the author presents the algorithms in a purely functional version of the Scheme programming language, which he makes available on his website. The book is supported with exercises, and it is suitable for undergraduate and graduate courses on programming techniques.
A programming course should concentrate as much as possible on a program's logical structure and design rather than simply show how to write code. The Functional Approach to Programming achieves this aim because logical concepts are evident and programs are transparent so can be written quickly and cleanly. In this book the authors emphasise the notions of function and function application which relate programming to familiar concepts from mathematics and logic. They introduce functional programming via examples but also explain what programs compute and how to reason about them. They show how the ideas can be implemented in the Caml language, a dialect of the ML family, and give examples of how complex programs from a variety of areas (such as arithmetic, tree algorithms, graph algorithms, text parsing and geometry) can be developed in close agreement with their specifications. Many exercises and examples are included throughout the book; solutions are also available.
Ideal for learning or reference, this book explains the five main principles of algorithm design and their implementation in Haskell.
Learn functional data structures and algorithms for your applications and bring their benefits to your work now About This Book Moving from object-oriented programming to functional programming? This book will help you get started with functional programming. Easy-to-understand explanations of practical topics will help you get started with functional data structures. Illustrative diagrams to explain the algorithms in detail. Get hands-on practice of Scala to get the most out of functional programming. Who This Book Is For This book is for those who have some experience in functional programming languages. The data structures in this book are primarily written in Scala, however implementing the algorithms in other functional languages should be straight forward. What You Will Learn Learn to think in the functional paradigm Understand common data structures and the associated algorithms, as well as the context in which they are commonly used Take a look at the runtime and space complexities with the O notation See how ADTs are implemented in a functional setting Explore the basic theme of immutability and persistent data structures Find out how the internal algorithms are redesigned to exploit structural sharing, so that the persistent data structures perform well, avoiding needless copying. Get to know functional features like lazy evaluation and recursion used to implement efficient algorithms Gain Scala best practices and idioms In Detail Functional data structures have the power to improve the codebase of an application and improve efficiency. With the advent of functional programming and with powerful functional languages such as Scala, Clojure and Elixir becoming part of important enterprise applications, functional data structures have gained an important place in the developer toolkit. Immutability is a cornerstone of functional programming. Immutable and persistent data structures are thread safe by definition and hence very appealing for writing robust concurrent programs. How do we express traditional algorithms in functional setting? Won't we end up copying too much? Do we trade performance for versioned data structures? This book attempts to answer these questions by looking at functional implementations of traditional algorithms. It begins with a refresher and consolidation of what functional programming is all about. Next, you'll get to know about Lists, the work horse data type for most functional languages. We show what structural sharing means and how it helps to make immutable data structures efficient and practical. Scala is the primary implementation languages for most of the examples. At times, we also present Clojure snippets to illustrate the underlying fundamental theme. While writing code, we use ADTs (abstract data types). Stacks, Queues, Trees and Graphs are all familiar ADTs. You will see how these ADTs are implemented in a functional setting. We look at implementation techniques like amortization and lazy evaluation to ensure efficiency. By the end of the book, you will be able to write efficient functional data structures and algorithms for your applications. Style and approach Step-by-step topics will help you get started with functional programming. Learn by doing with hands-on code snippets that give you practical experience of the subject.
This book is a revised edition of the monograph which appeared under the same title in the series Research Notes in Theoretical Computer Science, Pit man, in 1986. In addition to a general effort to improve typography, English, and presentation, the main novelty of this second edition is the integration of some new material. Part of it is mine (mostly jointly with coauthors). Here is brief guide to these additions. I have augmented the account of categorical combinatory logic with a description of the confluence properties of rewriting systems of categor ical combinators (Hardin, Yokouchi), and of the newly developed cal culi of explicit substitutions (Abadi, Cardelli, Curien, Hardin, Levy, and Rios), which are similar in spirit to the categorical combinatory logic, but are closer to the syntax of A-calculus (Section 1.2). The study of the full abstraction problem for PCF and extensions of it has been enriched with a new full abstraction result: the model of sequential algorithms is fully abstract with respect to an extension of PCF with a control operator (Cartwright, Felleisen, Curien). An order extensional model of error-sensitive sequential algorithms is also fully abstract for a corresponding extension of PCF with a control operator and errors (Sections 2.6 and 4.1). I suggest that sequential algorithms lend themselves to a decomposition of the function spaces that leads to models of linear logic (Lamarche, Curien), and that connects sequentiality with games (Joyal, Blass, Abramsky) (Sections 2.1 and 2.6).
Your guide to the functional programming paradigm Functional programming mainly sees use in math computations, including those used in Artificial Intelligence and gaming. This programming paradigm makes algorithms used for math calculations easier to understand and provides a concise method of coding algorithms by people who aren't developers. Current books on the market have a significant learning curve because they're written for developers, by developers—until now. Functional Programming for Dummies explores the differences between the pure (as represented by the Haskell language) and impure (as represented by the Python language) approaches to functional programming for readers just like you. The pure approach is best suited to researchers who have no desire to create production code but do need to test algorithms fully and demonstrate their usefulness to peers. The impure approach is best suited to production environments because it's possible to mix coding paradigms in a single application to produce a result more quickly. Functional Programming For Dummies uses this two-pronged approach to give you an all-in-one approach to a coding methodology that can otherwise be hard to grasp. Learn pure and impure when it comes to coding Dive into the processes that most functional programmers use to derive, analyze and prove the worth of algorithms Benefit from examples that are provided in both Python and Haskell Glean the expertise of an expert author who has written some of the market-leading programming books to date If you’re ready to massage data to understand how things work in new ways, you’ve come to the right place!
Several carefully revised lectures from the 6th International School on Functional Programming, AFP 2008, are presented in this valuable review. Topics include computation with Delta ML, spider spinning, reduction-based normalization and Haskell programming.
High Algorithms is a text geared to a junior level course in algorithms using Scheme as the programming language. Using the high- level language Scheme allows the author to make extensive use of concise yet highly readable source code or psuedocode for the implementation of all the algorithms covered in the book. This avoids a major weakness of other books currently used as texts for a course in algorithms. The resulting book covers all the traditional algorithms and introduces students to abstractions in a gradual and sensible manner. It is a light and lively presentation including prose descriptions, mathematical presntations and psuedocode for a comprehensive list of the major algorithms. The book lends itself to an accompanying lab on the topic and much supporting material both for teachers and readers or students is available at the accompanying website for the book.
