Learning Functional Programming in Go Pdf, Epub, Ebook
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Exploring Languages with Interpreters and Functional Programming Chapter 8
Exploring Languages with Interpreters and Functional Programming Chapter 8 H. Conrad Cunningham 24 September 2018 Contents 8 Evaluation Model 2 8.1 Chapter Introduction . .2 8.2 Referential Transparency Revisited . .2 8.3 Substitution Model . .3 8.4 Time and Space Complexity . .6 8.5 Termination . .7 8.6 What Next? . .7 8.7 Exercises . .8 8.8 Acknowledgements . .8 8.9 References . .9 8.10 Terms and Concepts . .9 Copyright (C) 2016, 2017, 2018, H. Conrad Cunningham Professor of Computer and Information Science University of Mississippi 211 Weir Hall P.O. Box 1848 University, MS 38677 (662) 915-5358 Browser Advisory: The HTML version of this textbook requires a browser that supports the display of MathML. A good choice as of September 2018 is a recent version of Firefox from Mozilla. 1 8 Evaluation Model 8.1 Chapter Introduction This chapter introduces an evaluation model applicable to Haskell programs. As in the previous chapters, this chapter focuses on use of first-order functions and primitive data types. A goal of this chapter and the next one is enable students to analyze Haskell functions to determine under what conditions they terminate normally and how efficient they are. This chapter presents the evaluation model and the next chapter informally analyzes simple functions in terms of time and space efficiency and termination. How can we evaluate (i.e. execute) an expression that “calls” a function like the fact1 function from Chapter 4? We do this by rewriting expressions using a substitution model, as we see in this chapter. This process depends upon a property of functional languages called referential transparency. -
Design Patterns Promote Reuse
Design Patterns Promote Reuse “A pattern describes a problem that occurs often, along with a tried solution to the problem” - Christopher Alexander, 1977 • Christopher Alexander’s 253 (civil) architectural patterns range from the creation of cities (2. distribution of towns) to particular building problems (232. roof cap) • A pattern language is an organized way of tackling an architectural problem using patterns Kinds of Patterns in Software • Architectural (“macroscale”) patterns • Model-view-controller • Pipe & Filter (e.g. compiler, Unix pipeline) • Event-based (e.g. interactive game) • Layering (e.g. SaaS technology stack) • Computation patterns • Fast Fourier transform • Structured & unstructured grids • Dense linear algebra • Sparse linear algebra • GoF (Gang of Four) Patterns: structural, creational, behavior The Gang of Four (GoF) • 23 structural design patterns • description of communicating objects & classes • captures common (and successful) solution to a category of related problem instances • can be customized to solve a specific (new) problem in that category • Pattern ≠ • individual classes or libraries (list, hash, ...) • full design—more like a blueprint for a design The GoF Pattern Zoo 1. Factory 13. Observer 14. Mediator 2. Abstract factory 15. Chain of responsibility 3. Builder Creation 16. Command 4. Prototype 17. Interpreter 18. Iterator 5. Singleton/Null obj 19. Memento (memoization) 6. Adapter Behavioral 20. State 21. Strategy 7. Composite 22. Template 8. Proxy 23. Visitor Structural 9. Bridge 10. Flyweight 11. -
Week 3: Scope and Evaluation Order Assignment 1 Has Been Posted!
Week 3: Scope and Evaluation Order CSC324 Principles of Programming Languages David Liu, Department of Computer Science Assignment 1 has been posted! Closures and static scope static (adjective) determined only by the program source code dynamic (adjective) determined only when the program is run E.g., referential transparency is a static property How are closures implemented? Are they static or dynamic? Or both? Function bodies can be processed statically (e.g., Haskell compiler generates code once per lambda). The closure environment (and therefore the closure itself) can only be generated dynamically. The closure depends only on where the function is evaluated, not where that function is called. (define (make-adder n) (lambda (x) (+ x n))) (define adder (make-adder 1)) (adder 100) So we can determine where each free identifier obtains its values statically, based on where its enclosing function is defined. scope (of an identifier) The parts of program code that may refer to that identifier. static (aka lexical) scope The scope of every identifier is determined by the structure of the source code (e.g., by nesting of lambdas and lets). Every identifier obtains its value from the closest enclosing expression that binds it. (define (make-adder n) (lambda (x) (+ x n))) (define adder (make-adder 1)) ; (0x..., {n: 1}) (let* ([n 100]) (adder 2)) Implementing static scope in an interpreter A simple interpreter (define/match (interpret env expr) [(_ (? number?)) expr] [(_ (? symbol?)) (hash-ref env expr)] [(_ (list '+ l r)) (+ (interpret env l) (interpret env r))]) A simple interpreter (define/match (interpret env expr) [(_ (? number?)) expr] [(_ (? symbol?)) (hash-ref env expr)] [(_ (list '+ l r)) (+ (interpret env l) (interpret env r))]) The environment is passed recursively when interpreting each subexpression. -
Reversible Programming with Negative and Fractional Types
9 A Computational Interpretation of Compact Closed Categories: Reversible Programming with Negative and Fractional Types CHAO-HONG CHEN, Indiana University, USA AMR SABRY, Indiana University, USA Compact closed categories include objects representing higher-order functions and are well-established as models of linear logic, concurrency, and quantum computing. We show that it is possible to construct such compact closed categories for conventional sum and product types by defining a dual to sum types, a negative type, and a dual to product types, a fractional type. Inspired by the categorical semantics, we define a sound operational semantics for negative and fractional types in which a negative type represents a computational effect that “reverses execution flow” and a fractional type represents a computational effect that“garbage collects” particular values or throws exceptions. Specifically, we extend a first-order reversible language of type isomorphisms with negative and fractional types, specify an operational semantics for each extension, and prove that each extension forms a compact closed category. We furthermore show that both operational semantics can be merged using the standard combination of backtracking and exceptions resulting in a smooth interoperability of negative and fractional types. We illustrate the expressiveness of this combination by writing a reversible SAT solver that uses back- tracking search along freshly allocated and de-allocated locations. The operational semantics, most of its meta-theoretic properties, and all examples are formalized in a supplementary Agda package. CCS Concepts: • Theory of computation → Type theory; Abstract machines; Operational semantics. Additional Key Words and Phrases: Abstract Machines, Duality of Computation, Higher-Order Reversible Programming, Termination Proofs, Type Isomorphisms ACM Reference Format: Chao-Hong Chen and Amr Sabry. -
Pattern Matching
Functional Programming Steven Lau March 2015 before function programming... https://www.youtube.com/watch?v=92WHN-pAFCs Models of computation ● Turing machine ○ invented by Alan Turing in 1936 ● Lambda calculus ○ invented by Alonzo Church in 1930 ● more... Turing machine ● A machine operates on an infinite tape (memory) and execute a program stored ● It may ○ read a symbol ○ write a symbol ○ move to the left cell ○ move to the right cell ○ change the machine’s state ○ halt Turing machine Have some fun http://www.google.com/logos/2012/turing-doodle-static.html http://www.ioi2012.org/wp-content/uploads/2011/12/Odometer.pdf http://wcipeg.com/problems/desc/ioi1211 Turing machine incrementer state symbol action next_state _____ state 0 __1__ state 1 0 _ or 0 write 1 1 _10__ state 2 __1__ state 1 0 1 write 0 2 _10__ state 0 __1__ state 0 _00__ state 2 1 _ left 0 __0__ state 2 _00__ state 0 __0__ state 0 1 0 or 1 right 1 100__ state 1 _10__ state 1 2 0 left 0 100__ state 1 _10__ state 1 100__ state 1 _10__ state 1 100__ state 1 _10__ state 0 100__ state 0 _11__ state 1 101__ state 1 _11__ state 1 101__ state 1 _11__ state 0 101__ state 0 λ-calculus Beware! ● think mathematical, not C++/Pascal ● (parentheses) are for grouping ● variables cannot be mutated ○ x = 1 OK ○ x = 2 NO ○ x = x + 1 NO λ-calculus Simplification 1 of 2: ● Only anonymous functions are used ○ f(x) = x2+1 f(1) = 12+1 = 2 is written as ○ (λx.x2+1)(1) = 12+1 = 2 note that f = λx.x2+1 λ-calculus Simplification 2 of 2: ● Only unary functions are used ○ a binary function can be written as a unary function that return another unary function ○ (λ(x,y).x+y)(1,2) = 1+2 = 3 is written as [(λx.(λy.x+y))(1)](2) = [(λy.1+y)](2) = 1+2 = 3 ○ this technique is known as Currying Haskell Curry λ-calculus ● A lambda term has 3 forms: ○ x ○ λx.A ○ AB where x is a variable, A and B are lambda terms. -
SI 413, Unit 3: Advanced Scheme
SI 413, Unit 3: Advanced Scheme Daniel S. Roche ([email protected]) Fall 2018 1 Pure Functional Programming Readings for this section: PLP, Sections 10.7 and 10.8 Remember there are two important characteristics of a “pure” functional programming language: • Referential Transparency. This fancy term just means that, for any expression in our program, the result of evaluating it will always be the same. In fact, any referentially transparent expression could be replaced with its value (that is, the result of evaluating it) without changing the program whatsoever. Notice that imperative programming is about as far away from this as possible. For example, consider the C++ for loop: for ( int i = 0; i < 10;++i) { /∗ some s t u f f ∗/ } What can we say about the “stuff” in the body of the loop? Well, it had better not be referentially transparent. If it is, then there’s no point in running over it 10 times! • Functions are First Class. Another way of saying this is that functions are data, just like any number or list. Functions are values, in fact! The specific privileges that a function earns by virtue of being first class include: 1) Functions can be given names. This is not a big deal; we can name functions in pretty much every programming language. In Scheme this just means we can do (define (f x) (∗ x 3 ) ) 2) Functions can be arguments to other functions. This is what you started to get into at the end of Lab 2. For starters, there’s the basic predicate procedure?: (procedure? +) ; #t (procedure? 10) ; #f (procedure? procedure?) ; #t 1 And then there are “higher-order functions” like map and apply: (apply max (list 5 3 10 4)) ; 10 (map sqrt (list 16 9 64)) ; '(4 3 8) What makes the functions “higher-order” is that one of their arguments is itself another function. -
Dependency Injection in Unity3d
Dependency Injection in Unity3D Niko Parviainen Bachelor’s thesis March 2017 Technology, communication and transport Degree Programme in Software Engineering Description Author(s) Type of publication Date Parviainen, Niko Bachelor’s thesis March 2017 Language of publication: English Number of pages Permission for web publi- 57 cation: x Title of publication Dependency Injection in Unity3D Degree programme Degree Programme in Software Engineering Supervisor(s) Rantala, Ari Hämäläinen, Raija Assigned by Psyon Games Oy Abstract The objective was to find out how software design patterns and principles are applied to game development to achieve modular design. The tasks of the research were to identify the dependency management problem of a modular design, find out what the solutions offered by Unity3D are, find out what the dependency injection pattern is and how it is used in Unity3D environment. Dependency management in Unity3D and the dependency injection pattern were studied. Problems created by Unity3D’s solutions were introduced with examples. Dependency in- jection pattern was introduced with examples and demonstrated by implementing an ex- ample game using one of the available third-party frameworks. The aim of the example game was to clarify if the use of dependency injection brings modularity in Unity3D envi- ronment and what the cost of using it is. The principles of SOLID were introduced with generic examples and used to assist depend- ency injection to further increase the modularity by bringing the focus on class design. Dependency injection with the help of SOLID principles increased the modularity by loosely coupling classes even though slightly increasing the overall complexity of the architecture. -
Let's Get Functional
5 LET’S GET FUNCTIONAL I’ve mentioned several times that F# is a functional language, but as you’ve learned from previous chapters you can build rich applications in F# without using any functional techniques. Does that mean that F# isn’t really a functional language? No. F# is a general-purpose, multi paradigm language that allows you to program in the style most suited to your task. It is considered a functional-first lan- guage, meaning that its constructs encourage a functional style. In other words, when developing in F# you should favor functional approaches whenever possible and switch to other styles as appropriate. In this chapter, we’ll see what functional programming really is and how functions in F# differ from those in other languages. Once we’ve estab- lished that foundation, we’ll explore several data types commonly used with functional programming and take a brief side trip into lazy evaluation. The Book of F# © 2014 by Dave Fancher What Is Functional Programming? Functional programming takes a fundamentally different approach toward developing software than object-oriented programming. While object-oriented programming is primarily concerned with managing an ever-changing system state, functional programming emphasizes immutability and the application of deterministic functions. This difference drastically changes the way you build software, because in object-oriented programming you’re mostly concerned with defining classes (or structs), whereas in functional programming your focus is on defining functions with particular emphasis on their input and output. F# is an impure functional language where data is immutable by default, though you can still define mutable data or cause other side effects in your functions. -
Facet: a Pattern for Dynamic Interfaces
Facet: A pattern for dynamic interfaces Author: Eric Crahen SUNY at Buffalo CSE Department Amherst, NY 14260 201 Bell Hall 716-645-3180 <[email protected]> Context: Wherever it is desirable to create a context sensitive interface in order to modify or control the apparent behavior if an object. Problem: How can I modify the behavior of an existing object so that different behaviors are shown under different circumstances; and yet still maintain a clean separation between the policy (when each behavior is available) and implementation of each behavior allowing them to be developed independently of one another? Forces: Interfaces provide an essential level of abstraction to object oriented programming. Generally, objects are able define aspects of their function very well using interfaces. At times, this may not be enough. When dealing with two or more classes whose responsibilities are distinctly separate, but whose behavior is closely related, classes can begin to resist modularization. For example, adding security to an application means inserting code that performs security checks into numerous locations in existing classes. Clearly, these responsibilities are distinct; the original classes being responsible for the tasks they were designed to perform, and the security classes being responsible for providing access control. However, making those original classes secure means intermingling code that deals with security. When the classes dealing with security are changed many classes are going to be impacted. One method of adding new behavior to an existing class might be to simply create a subclass and embed that new behavior. In the security example, this would mean creating a subclass for each class that needs to be secure and adding calls to the security code. -
Lambda Calculus and Functional Programming
Global Journal of Researches in Engineering Vol. 10 Issue 2 (Ver 1.0) June 2010 P a g e | 47 Lambda Calculus and Functional Programming Anahid Bassiri1Mohammad Reza. Malek2 GJRE Classification (FOR) 080299, 010199, 010203, Pouria Amirian3 010109 Abstract-The lambda calculus can be thought of as an idealized, Basis concept of a Turing machine is the present day Von minimalistic programming language. It is capable of expressing Neumann computers. Conceptually these are Turing any algorithm, and it is this fact that makes the model of machines with random access registers. Imperative functional programming an important one. This paper is programming languages such as FORTRAN, Pascal etcetera focused on introducing lambda calculus and its application. As as well as all the assembler languages are based on the way an application dikjestra algorithm is implemented using a Turing machine is instructed by a sequence of statements. lambda calculus. As program shows algorithm is more understandable using lambda calculus in comparison with In addition functional programming languages, like other imperative languages. Miranda, ML etcetera, are based on the lambda calculus. Functional programming is a programming paradigm that I. INTRODUCTION treats computation as the evaluation of mathematical ambda calculus (λ-calculus) is a useful device to make functions and avoids state and mutable data. It emphasizes L the theories realizable. Lambda calculus, introduced by the application of functions, in contrast with the imperative Alonzo Church and Stephen Cole Kleene in the 1930s is a programming style that emphasizes changes in state. formal system designed to investigate function definition, Lambda calculus provides a theoretical framework for function application and recursion in mathematical logic and describing functions and their evaluation. -
Dependency Injection with Unity
D EPEN DEPENDENCY INJECTION WITH UNITY Over the years software systems have evolutionarily become more and more patterns & practices D ENCY complex. One of the techniques for dealing with this inherent complexity Proven practices for predictable results of software systems is dependency injection – a design pattern that I allows the removal of hard-coded dependencies and makes it possible to Save time and reduce risk on your NJECT assemble a service by changing dependencies easily, whether at run-time software development projects by or compile-time. It promotes code reuse and loosely-coupled design which incorporating patterns & practices, I leads to more easily maintainable and flexible code. Microsoft’s applied engineering ON guidance that includes both production The guide you are holding in your hands is a primer on using dependency quality source code and documentation. W I injection with Unity – a lightweight extensible dependency injection TH DEPENDENCY INJECTION container built by the Microsoft patterns & practices team. It covers The guidance is designed to help U software development teams: various styles of dependency injection and also additional capabilities N I of Unity container, such as object lifetime management, interception, Make critical design and technology TY and registration by convention. It also discusses the advanced topics of selection decisions by highlighting WITH UNITY enhancing Unity with your custom extensions. the appropriate solution architectures, technologies, and Microsoft products The guide contains plenty of trade-off discussions and tips and tricks for for common scenarios managing your application cross-cutting concerns and making the most out of both dependency injection and Unity. These are accompanied by a Understand the most important Dominic Betts real world example that will help you master the techniques. -
Notes on Functional Programming with Haskell
Notes on Functional Programming with Haskell H. Conrad Cunningham [email protected] Multiparadigm Software Architecture Group Department of Computer and Information Science University of Mississippi 201 Weir Hall University, Mississippi 38677 USA Fall Semester 2014 Copyright c 1994, 1995, 1997, 2003, 2007, 2010, 2014 by H. Conrad Cunningham Permission to copy and use this document for educational or research purposes of a non-commercial nature is hereby granted provided that this copyright notice is retained on all copies. All other rights are reserved by the author. H. Conrad Cunningham, D.Sc. Professor and Chair Department of Computer and Information Science University of Mississippi 201 Weir Hall University, Mississippi 38677 USA [email protected] PREFACE TO 1995 EDITION I wrote this set of lecture notes for use in the course Functional Programming (CSCI 555) that I teach in the Department of Computer and Information Science at the Uni- versity of Mississippi. The course is open to advanced undergraduates and beginning graduate students. The first version of these notes were written as a part of my preparation for the fall semester 1993 offering of the course. This version reflects some restructuring and revision done for the fall 1994 offering of the course|or after completion of the class. For these classes, I used the following resources: Textbook { Richard Bird and Philip Wadler. Introduction to Functional Program- ming, Prentice Hall International, 1988 [2]. These notes more or less cover the material from chapters 1 through 6 plus selected material from chapters 7 through 9. Software { Gofer interpreter version 2.30 (2.28 in 1993) written by Mark P.