Crossing the Gap from Imperative to Functional Programming Through Refactoring
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Functional Languages
Functional Programming Languages (FPL) 1. Definitions................................................................... 2 2. Applications ................................................................ 2 3. Examples..................................................................... 3 4. FPL Characteristics:.................................................... 3 5. Lambda calculus (LC)................................................. 4 6. Functions in FPLs ....................................................... 7 7. Modern functional languages...................................... 9 8. Scheme overview...................................................... 11 8.1. Get your own Scheme from MIT...................... 11 8.2. General overview.............................................. 11 8.3. Data Typing ...................................................... 12 8.4. Comments ......................................................... 12 8.5. Recursion Instead of Iteration........................... 13 8.6. Evaluation ......................................................... 14 8.7. Storing and using Scheme code ........................ 14 8.8. Variables ........................................................... 15 8.9. Data types.......................................................... 16 8.10. Arithmetic functions ......................................... 17 8.11. Selection functions............................................ 18 8.12. Iteration............................................................. 23 8.13. Defining functions ........................................... -
Higher-Order Functions 15-150: Principles of Functional Programming – Lecture 13
Higher-order Functions 15-150: Principles of Functional Programming { Lecture 13 Giselle Reis By now you might feel like you have a pretty good idea of what is going on in functional program- ming, but in reality we have used only a fragment of the language. In this lecture we see what more we can do and what gives the name functional to this paradigm. Let's take a step back and look at ML's typing system: we have basic types (such as int, string, etc.), tuples of types (t*t' ) and functions of a type to a type (t ->t' ). In a grammar style (where α is a basic type): τ ::= α j τ ∗ τ j τ ! τ What types allowed by this grammar have we not used so far? Well, we could, for instance, have a function below a tuple. Or even a function within a function, couldn't we? The following are completely valid types: int*(int -> int) int ->(int -> int) (int -> int) -> int The first one is a pair in which the first element is an integer and the second one is a function from integers to integers. The second one is a function from integers to functions (which have type int -> int). The third type is a function from functions to integers. The two last types are examples of higher-order functions1, i.e., a function which: • receives a function as a parameter; or • returns a function. Functions can be used like any other value. They are first-class citizens. Maybe this seems strange at first, but I am sure you have used higher-order functions before without noticing it. -
C++ Programming: Program Design Including Data Structures, Fifth Edition
C++ Programming: From Problem Analysis to Program Design, Fifth Edition Chapter 5: Control Structures II (Repetition) Objectives In this chapter, you will: • Learn about repetition (looping) control structures • Explore how to construct and use count- controlled, sentinel-controlled, flag- controlled, and EOF-controlled repetition structures • Examine break and continue statements • Discover how to form and use nested control structures C++ Programming: From Problem Analysis to Program Design, Fifth Edition 2 Objectives (cont'd.) • Learn how to avoid bugs by avoiding patches • Learn how to debug loops C++ Programming: From Problem Analysis to Program Design, Fifth Edition 3 Why Is Repetition Needed? • Repetition allows you to efficiently use variables • Can input, add, and average multiple numbers using a limited number of variables • For example, to add five numbers: – Declare a variable for each number, input the numbers and add the variables together – Create a loop that reads a number into a variable and adds it to a variable that contains the sum of the numbers C++ Programming: From Problem Analysis to Program Design, Fifth Edition 4 while Looping (Repetition) Structure • The general form of the while statement is: while is a reserved word • Statement can be simple or compound • Expression acts as a decision maker and is usually a logical expression • Statement is called the body of the loop • The parentheses are part of the syntax C++ Programming: From Problem Analysis to Program Design, Fifth Edition 5 while Looping (Repetition) -
Compiler Construction Assignment 3 – Spring 2018
Compiler Construction Assignment 3 { Spring 2018 Robert van Engelen µc for the JVM µc (micro-C) is a small C-inspired programming language. In this assignment we will implement a compiler in C++ for µc. The compiler compiles µc programs to java class files for execution with the Java virtual machine. To implement the compiler, we can reuse the same concepts in the code-generation parts that were done in programming assignment 1 and reuse parts of the lexical analyzer you implemented in programming assignment 2. We will implement a new parser based on Yacc/Bison. This new parser utilizes translation schemes defined in Yacc grammars to emit Java bytecode. In the next programming assignment (the last assignment following this assignment) we will further extend the capabilities of our µc compiler by adding static semantics such as data types, apply type checking, and implement scoping rules for functions and blocks. Download Download the Pr3.zip file from http://www.cs.fsu.edu/~engelen/courses/COP5621/Pr3.zip. After unzipping you will get the following files Makefile A makefile bytecode.c The bytecode emitter (same as Pr1) bytecode.h The bytecode definitions (same as Pr1) error.c Error reporter global.h Global definitions init.c Symbol table initialization javaclass.c Java class file operations (same as Pr1) javaclass.h Java class file definitions (same as Pr1) mycc.l *) Lex specification mycc.y *) Yacc specification and main program symbol.c *) Symbol table operations test#.uc A number of µc test programs The files marked ∗) are incomplete. For this assignment you are required to complete these files. -
PDF Python 3
Python for Everybody Exploring Data Using Python 3 Charles R. Severance 5.7. LOOP PATTERNS 61 In Python terms, the variable friends is a list1 of three strings and the for loop goes through the list and executes the body once for each of the three strings in the list resulting in this output: Happy New Year: Joseph Happy New Year: Glenn Happy New Year: Sally Done! Translating this for loop to English is not as direct as the while, but if you think of friends as a set, it goes like this: “Run the statements in the body of the for loop once for each friend in the set named friends.” Looking at the for loop, for and in are reserved Python keywords, and friend and friends are variables. for friend in friends: print('Happy New Year:', friend) In particular, friend is the iteration variable for the for loop. The variable friend changes for each iteration of the loop and controls when the for loop completes. The iteration variable steps successively through the three strings stored in the friends variable. 5.7 Loop patterns Often we use a for or while loop to go through a list of items or the contents of a file and we are looking for something such as the largest or smallest value of the data we scan through. These loops are generally constructed by: • Initializing one or more variables before the loop starts • Performing some computation on each item in the loop body, possibly chang- ing the variables in the body of the loop • Looking at the resulting variables when the loop completes We will use a list of numbers to demonstrate the concepts and construction of these loop patterns. -
The Machine That Builds Itself: How the Strengths of Lisp Family
Khomtchouk et al. OPINION NOTE The Machine that Builds Itself: How the Strengths of Lisp Family Languages Facilitate Building Complex and Flexible Bioinformatic Models Bohdan B. Khomtchouk1*, Edmund Weitz2 and Claes Wahlestedt1 *Correspondence: [email protected] Abstract 1Center for Therapeutic Innovation and Department of We address the need for expanding the presence of the Lisp family of Psychiatry and Behavioral programming languages in bioinformatics and computational biology research. Sciences, University of Miami Languages of this family, like Common Lisp, Scheme, or Clojure, facilitate the Miller School of Medicine, 1120 NW 14th ST, Miami, FL, USA creation of powerful and flexible software models that are required for complex 33136 and rapidly evolving domains like biology. We will point out several important key Full list of author information is features that distinguish languages of the Lisp family from other programming available at the end of the article languages and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSL): languages which are specialized to a particular area and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the “programmable programming language.” We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and AI research in bioinformatics and computational biology. -
Typescript Language Specification
TypeScript Language Specification Version 1.8 January, 2016 Microsoft is making this Specification available under the Open Web Foundation Final Specification Agreement Version 1.0 ("OWF 1.0") as of October 1, 2012. The OWF 1.0 is available at http://www.openwebfoundation.org/legal/the-owf-1-0-agreements/owfa-1-0. TypeScript is a trademark of Microsoft Corporation. Table of Contents 1 Introduction ................................................................................................................................................................................... 1 1.1 Ambient Declarations ..................................................................................................................................................... 3 1.2 Function Types .................................................................................................................................................................. 3 1.3 Object Types ...................................................................................................................................................................... 4 1.4 Structural Subtyping ....................................................................................................................................................... 6 1.5 Contextual Typing ............................................................................................................................................................ 7 1.6 Classes ................................................................................................................................................................................. -
Functional Programming Laboratory 1 Programming Paradigms
Intro 1 Functional Programming Laboratory C. Beeri 1 Programming Paradigms A programming paradigm is an approach to programming: what is a program, how are programs designed and written, and how are the goals of programs achieved by their execution. A paradigm is an idea in pure form; it is realized in a language by a set of constructs and by methodologies for using them. Languages sometimes combine several paradigms. The notion of paradigm provides a useful guide to understanding programming languages. The imperative paradigm underlies languages such as Pascal and C. The object-oriented paradigm is embodied in Smalltalk, C++ and Java. These are probably the paradigms known to the students taking this lab. We introduce functional programming by comparing it to them. 1.1 Imperative and object-oriented programming Imperative programming is based on a simple construct: A cell is a container of data, whose contents can be changed. A cell is an abstraction of a memory location. It can store data, such as integers or real numbers, or addresses of other cells. The abstraction hides the size bounds that apply to real memory, as well as the physical address space details. The variables of Pascal and C denote cells. The programming construct that allows to change the contents of a cell is assignment. In the imperative paradigm a program has, at each point of its execution, a state represented by a collection of cells and their contents. This state changes as the program executes; assignment statements change the contents of cells, other statements create and destroy cells. Yet others, such as conditional and loop statements allow the programmer to direct the control flow of the program. -
7. Control Flow First?
Copyright (C) R.A. van Engelen, FSU Department of Computer Science, 2000-2004 Ordering Program Execution: What is Done 7. Control Flow First? Overview Categories for specifying ordering in programming languages: Expressions 1. Sequencing: the execution of statements and evaluation of Evaluation order expressions is usually in the order in which they appear in a Assignments program text Structured and unstructured flow constructs 2. Selection (or alternation): a run-time condition determines the Goto's choice among two or more statements or expressions Sequencing 3. Iteration: a statement is repeated a number of times or until a Selection run-time condition is met Iteration and iterators 4. Procedural abstraction: subroutines encapsulate collections of Recursion statements and subroutine calls can be treated as single Nondeterminacy statements 5. Recursion: subroutines which call themselves directly or indirectly to solve a problem, where the problem is typically defined in terms of simpler versions of itself 6. Concurrency: two or more program fragments executed in parallel, either on separate processors or interleaved on a single processor Note: Study Chapter 6 of the textbook except Section 7. Nondeterminacy: the execution order among alternative 6.6.2. constructs is deliberately left unspecified, indicating that any alternative will lead to a correct result Expression Syntax Expression Evaluation Ordering: Precedence An expression consists of and Associativity An atomic object, e.g. number or variable The use of infix, prefix, and postfix notation leads to ambiguity An operator applied to a collection of operands (or as to what is an operand of what arguments) which are expressions Fortran example: a+b*c**d**e/f Common syntactic forms for operators: The choice among alternative evaluation orders depends on Function call notation, e.g. -
Scala Tutorial
Scala Tutorial SCALA TUTORIAL Simply Easy Learning by tutorialspoint.com tutorialspoint.com i ABOUT THE TUTORIAL Scala Tutorial Scala is a modern multi-paradigm programming language designed to express common programming patterns in a concise, elegant, and type-safe way. Scala has been created by Martin Odersky and he released the first version in 2003. Scala smoothly integrates features of object-oriented and functional languages. This tutorial gives a great understanding on Scala. Audience This tutorial has been prepared for the beginners to help them understand programming Language Scala in simple and easy steps. After completing this tutorial, you will find yourself at a moderate level of expertise in using Scala from where you can take yourself to next levels. Prerequisites Scala Programming is based on Java, so if you are aware of Java syntax, then it's pretty easy to learn Scala. Further if you do not have expertise in Java but you know any other programming language like C, C++ or Python, then it will also help in grasping Scala concepts very quickly. Copyright & Disclaimer Notice All the content and graphics on this tutorial are the property of tutorialspoint.com. Any content from tutorialspoint.com or this tutorial may not be redistributed or reproduced in any way, shape, or form without the written permission of tutorialspoint.com. Failure to do so is a violation of copyright laws. This tutorial may contain inaccuracies or errors and tutorialspoint provides no guarantee regarding the accuracy of the site or its contents including this tutorial. If you discover that the tutorialspoint.com site or this tutorial content contains some errors, please contact us at [email protected] TUTORIALS POINT Simply Easy Learning Table of Content Scala Tutorial .......................................................................... -
Repetition Structures
24785_CH06_BRONSON.qrk 11/10/04 9:05 M Page 301 Repetition Structures 6.1 Introduction Goals 6.2 Do While Loops 6.3 Interactive Do While Loops 6.4 For/Next Loops 6.5 Nested Loops 6.6 Exit-Controlled Loops 6.7 Focus on Program Design and Implementation: After-the- Fact Data Validation and Creating Keyboard Shortcuts 6.8 Knowing About: Programming Costs 6.9 Common Programming Errors and Problems 6.10 Chapter Review 24785_CH06_BRONSON.qrk 11/10/04 9:05 M Page 302 302 | Chapter 6: Repetition Structures The applications examined so far have illustrated the programming concepts involved in input, output, assignment, and selection capabilities. By this time you should have gained enough experience to be comfortable with these concepts and the mechanics of implementing them using Visual Basic. However, many problems require a repetition capability, in which the same calculation or sequence of instructions is repeated, over and over, using different sets of data. Examples of such repetition include continual checking of user data entries until an acceptable entry, such as a valid password, is made; counting and accumulating running totals; and recurring acceptance of input data and recalculation of output values that only stop upon entry of a designated value. This chapter explores the different methods that programmers use to construct repeating sections of code and how they can be implemented in Visual Basic. A repeated procedural section of code is commonly called a loop, because after the last statement in the code is executed, the program branches, or loops back to the first statement and starts another repetition. -
Functional and Imperative Object-Oriented Programming in Theory and Practice
Uppsala universitet Inst. för informatik och media Functional and Imperative Object-Oriented Programming in Theory and Practice A Study of Online Discussions in the Programming Community Per Jernlund & Martin Stenberg Kurs: Examensarbete Nivå: C Termin: VT-19 Datum: 14-06-2019 Abstract Functional programming (FP) has progressively become more prevalent and techniques from the FP paradigm has been implemented in many different Imperative object-oriented programming (OOP) languages. However, there is no indication that OOP is going out of style. Nevertheless the increased popularity in FP has sparked new discussions across the Internet between the FP and OOP communities regarding a multitude of related aspects. These discussions could provide insights into the questions and challenges faced by programmers today. This thesis investigates these online discussions in a small and contemporary scale in order to identify the most discussed aspect of FP and OOP. Once identified the statements and claims made by various discussion participants were selected and compared to literature relating to the aspects and the theory behind the paradigms in order to determine whether there was any discrepancies between practitioners and theory. It was done in order to investigate whether the practitioners had different ideas in the form of best practices that could influence theories. The most discussed aspect within FP and OOP was immutability and state relating primarily to the aspects of concurrency and performance. This thesis presents a selection of representative quotes that illustrate the different points of view held by groups in the community and then addresses those claims by investigating what is said in literature.