1 Think Python How to Think Like a Computer Scientist Version
3 Think Python How to Think Like a Computer Scientist Version Allen Downey Green Tea Press Needham, Massachusetts
4 Copyright 2012 Allen Downey. Green Tea Press 9 Washburn Ave Needham MA Permission is granted to copy, distribute, and/or modify this document under the terms of the Creative Commons Attribution-NonCommercial 3.0 Unported License, which is available at http: //creativecommons.org/licenses/by-nc/3.0/. The original form of this book is LATEX source code. Compiling this LATEX source has the effect of generating a device-independent representation of a textbook, which can be converted to other formats and printed. The LATEX source for this book is available from
5 Preface The strange history of this book In January 1999 I was preparing to teach an introductory programming class in Java. I had taught it three times and I was getting frustrated. The failure rate in the class was too high and, even for students who succeeded, the overall level of achievement was too low. One of the problems I saw was the books. They were too big, with too much unnecessary detail about Java, and not enough high-level guidance about how to program. And they all suffered from the trap door effect: they would start out easy, proceed gradually, and then somewhere around Chapter 5 the bottom would fall out. The students would get too much new material, too fast, and I would spend the rest of the semester picking up the pieces. Two weeks before the first day of classes, I decided to write my own book. My goals were: Keep it short. It is better for students to read 10 pages than not read 50 pages. Be careful with vocabulary. I tried to minimize the jargon and define each term at first use. Build gradually. To avoid trap doors, I took the most difficult topics and split them into a series of small steps. Focus on programming, not the programming language. I included the minimum useful subset of Java and left out the rest. I needed a title, so on a whim I chose How to Think Like a Computer Scientist. My first version was rough, but it worked. Students did the reading, and they understood enough that I could spend class time on the hard topics, the interesting topics and (most important) letting the students practice. I released the book under the GNU Free Documentation License, which allows users to copy, modify, and distribute the book. What happened next is the cool part. Jeff Elkner, a high school teacher in Virginia, adopted my book and translated it into Python. He sent me a copy of his translation, and I had the unusual experience of learning Python by reading my own book. As Green Tea Press, I published the first Python version in In 2003 I started teaching at Olin College and I got to teach Python for the first time. The contrast with Java was striking. Students struggled less, learned more, worked on more interesting projects, and generally had a lot more fun.
6 vi Chapter 0. Preface Over the last nine years I continued to develop the book, correcting errors, improving some of the examples and adding material, especially exercises. The result is this book, now with the less grandiose title Think Python. Some of the changes are: I added a section about debugging at the end of each chapter. These sections present general techniques for finding and avoiding bugs, and warnings about Python pitfalls. I added more exercises, ranging from short tests of understanding to a few substantial projects. And I wrote solutions for most of them. I added a series of case studies longer examples with exercises, solutions, and discussion. Some are based on Swampy, a suite of Python programs I wrote for use in my classes. Swampy, code examples, and some solutions are available from I expanded the discussion of program development plans and basic design patterns. I added appendices about debugging, analysis of algorithms, and UML diagrams with Lumpy. I hope you enjoy working with this book, and that it helps you learn to program and think, at least a little bit, like a computer scientist. Allen B. Downey Needham MA Allen Downey is a Professor of Computer Science at the Franklin W. Olin College of Engineering. Acknowledgments Many thanks to Jeff Elkner, who translated my Java book into Python, which got this project started and introduced me to what has turned out to be my favorite language. Thanks also to Chris Meyers, who contributed several sections to How to Think Like a Computer Scientist. Thanks to the Free Software Foundation for developing the GNU Free Documentation License, which helped make my collaboration with Jeff and Chris possible, and Creative Commons for the license I am using now. Thanks to the editors at Lulu who worked on How to Think Like a Computer Scientist. Thanks to all the students who worked with earlier versions of this book and all the contributors (listed below) who sent in corrections and suggestions.
7 vii Contributor List More than 100 sharp-eyed and thoughtful readers have sent in suggestions and corrections over the past few years. Their contributions, and enthusiasm for this project, have been a huge help. If you have a suggestion or correction, please send to If I make a change based on your feedback, I will add you to the contributor list (unless you ask to be omitted). If you include at least part of the sentence the error appears in, that makes it easy for me to search. Page and section numbers are fine, too, but not quite as easy to work with. Thanks! Lloyd Hugh Allen sent in a correction to Section 8.4. Yvon Boulianne sent in a correction of a semantic error in Chapter 5. Fred Bremmer submitted a correction in Section 2.1. Jonah Cohen wrote the Perl scripts to convert the LaTeX source for this book into beautiful HTML. Michael Conlon sent in a grammar correction in Chapter 2 and an improvement in style in Chapter 1, and he initiated discussion on the technical aspects of interpreters. Benoit Girard sent in a correction to a humorous mistake in Section 5.6. Courtney Gleason and Katherine Smith wrote horsebet.py, which was used as a case study in an earlier version of the book. Their program can now be found on the website. Lee Harr submitted more corrections than we have room to list here, and indeed he should be listed as one of the principal editors of the text. James Kaylin is a student using the text. He has submitted numerous corrections. David Kershaw fixed the broken cattwice function in Section Eddie Lam has sent in numerous corrections to Chapters 1, 2, and 3. He also fixed the Makefile so that it creates an index the first time it is run and helped us set up a versioning scheme. Man-Yong Lee sent in a correction to the example code in Section 2.4. David Mayo pointed out that the word unconsciously" in Chapter 1 needed to be changed to subconsciously". Chris McAloon sent in several corrections to Sections 3.9 and Matthew J. Moelter has been a long-time contributor who sent in numerous corrections and suggestions to the book. Simon Dicon Montford reported a missing function definition and several typos in Chapter 3. He also found errors in the increment function in Chapter 13. John Ouzts corrected the definition of return value" in Chapter 3. Kevin Parks sent in valuable comments and suggestions as to how to improve the distribution of the book. David Pool sent in a typo in the glossary of Chapter 1, as well as kind words of encouragement. Michael Schmitt sent in a correction to the chapter on files and exceptions.
8 viii Chapter 0. Preface Robin Shaw pointed out an error in Section 13.1, where the printtime function was used in an example without being defined. Paul Sleigh found an error in Chapter 7 and a bug in Jonah Cohen s Perl script that generates HTML from LaTeX. Craig T. Snydal is testing the text in a course at Drew University. He has contributed several valuable suggestions and corrections. Ian Thomas and his students are using the text in a programming course. They are the first ones to test the chapters in the latter half of the book, and they have made numerous corrections and suggestions. Keith Verheyden sent in a correction in Chapter 3. Peter Winstanley let us know about a longstanding error in our Latin in Chapter 3. Chris Wrobel made corrections to the code in the chapter on file I/O and exceptions. Moshe Zadka has made invaluable contributions to this project. In addition to writing the first draft of the chapter on Dictionaries, he provided continual guidance in the early stages of the book. Christoph Zwerschke sent several corrections and pedagogic suggestions, and explained the difference between gleich and selbe. James Mayer sent us a whole slew of spelling and typographical errors, including two in the contributor list. Hayden McAfee caught a potentially confusing inconsistency between two examples. Angel Arnal is part of an international team of translators working on the Spanish version of the text. He has also found several errors in the English version. Tauhidul Hoque and Lex Berezhny created the illustrations in Chapter 1 and improved many of the other illustrations. Dr. Michele Alzetta caught an error in Chapter 8 and sent some interesting pedagogic comments and suggestions about Fibonacci and Old Maid. Andy Mitchell caught a typo in Chapter 1 and a broken example in Chapter 2. Kalin Harvey suggested a clarification in Chapter 7 and caught some typos. Christopher P. Smith caught several typos and helped us update the book for Python 2.2. David Hutchins caught a typo in the Foreword. Gregor Lingl is teaching Python at a high school in Vienna, Austria. He is working on a German translation of the book, and he caught a couple of bad errors in Chapter 5. Julie Peters caught a typo in the Preface. Florin Oprina sent in an improvement in maketime, a correction in printtime, and a nice typo. D. J. Webre suggested a clarification in Chapter 3. Ken found a fistful of errors in Chapters 8, 9 and 11. Ivo Wever caught a typo in Chapter 5 and suggested a clarification in Chapter 3. Curtis Yanko suggested a clarification in Chapter 2.
9 ix Ben Logan sent in a number of typos and problems with translating the book into HTML. Jason Armstrong saw the missing word in Chapter 2. Louis Cordier noticed a spot in Chapter 16 where the code didn t match the text. Brian Cain suggested several clarifications in Chapters 2 and 3. Rob Black sent in a passel of corrections, including some changes for Python 2.2. Jean-Philippe Rey at Ecole Centrale Paris sent a number of patches, including some updates for Python 2.2 and other thoughtful improvements. Jason Mader at George Washington University made a number of useful suggestions and corrections. Jan Gundtofte-Bruun reminded us that a error is an error. Abel David and Alexis Dinno reminded us that the plural of matrix is matrices, not matrixes. This error was in the book for years, but two readers with the same initials reported it on the same day. Weird. Charles Thayer encouraged us to get rid of the semi-colons we had put at the ends of some statements and to clean up our use of argument and parameter. Roger Sperberg pointed out a twisted piece of logic in Chapter 3. Sam Bull pointed out a confusing paragraph in Chapter 2. Andrew Cheung pointed out two instances of use before def. C. Corey Capel spotted the missing word in the Third Theorem of Debugging and a typo in Chapter 4. Alessandra helped clear up some Turtle confusion. Wim Champagne found a brain-o in a dictionary example. Douglas Wright pointed out a problem with floor division in arc. Jared Spindor found some jetsam at the end of a sentence. Lin Peiheng sent a number of very helpful suggestions. Ray Hagtvedt sent in two errors and a not-quite-error. Torsten Hübsch pointed out an inconsistency in Swampy. Inga Petuhhov corrected an example in Chapter 14. Arne Babenhauserheide sent several helpful corrections. Mark E. Casida is is good at spotting repeated words. Scott Tyler filled in a that was missing. And then sent in a heap of corrections. Gordon Shephard sent in several corrections, all in separate s. Andrew Turner spotted an error in Chapter 8. Adam Hobart fixed a problem with floor division in arc.
10 x Chapter 0. Preface Daryl Hammond and Sarah Zimmerman pointed out that I served up math.pi too early. And Zim spotted a typo. George Sass found a bug in a Debugging section. Brian Bingham suggested Exercise Leah Engelbert-Fenton pointed out that I used tuple as a variable name, contrary to my own advice. And then found a bunch of typos and a use before def. Joe Funke spotted a typo. Chao-chao Chen found an inconsistency in the Fibonacci example. Jeff Paine knows the difference between space and spam. Lubos Pintes sent in a typo. Gregg Lind and Abigail Heithoff suggested Exercise Max Hailperin has sent in a number of corrections and suggestions. Max is one of the authors of the extraordinary Concrete Abstractions, which you might want to read when you are done with this book. Chotipat Pornavalai found an error in an error message. Stanislaw Antol sent a list of very helpful suggestions. Eric Pashman sent a number of corrections for Chapters Miguel Azevedo found some typos. Jianhua Liu sent in a long list of corrections. Nick King found a missing word. Martin Zuther sent a long list of suggestions. Adam Zimmerman found an inconsistency in my instance of an instance and several other errors. Ratnakar Tiwari suggested a footnote explaining degenerate triangles. Anurag Goel suggested another solution for is_abecedarian and sent some additional corrections. And he knows how to spell Jane Austen. Kelli Kratzer spotted one of the typos. Mark Griffiths pointed out a confusing example in Chapter 3. Roydan Ongie found an error in my Newton s method. Patryk Wolowiec helped me with a problem in the HTML version. Mark Chonofsky told me about a new keyword in Python 3. Russell Coleman helped me with my geometry. Wei Huang spotted several typographical errors. Karen Barber spotted the the oldest typo in the book.
11 xi Nam Nguyen found a typo and pointed out that I used the Decorator pattern but didn t mention it by name. Stéphane Morin sent in several corrections and suggestions. Paul Stoop corrected a typo in uses_only. Eric Bronner pointed out a confusion in the discussion of the order of operations. Alexandros Gezerlis set a new standard for the number and quality of suggestions he submitted. We are deeply grateful! Gray Thomas knows his right from his left. Giovanni Escobar Sosa sent a long list of corrections and suggestions. Alix Etienne fixed one of the URLs. Kuang He found a typo. Daniel Neilson corrected an error about the order of operations. Will McGinnis pointed out that polyline was defined differently in two places. Swarup Sahoo spotted a missing semi-colon. Frank Hecker pointed out an exercise that was under-specified, and some broken links. Animesh B helped me clean up a confusing example. Martin Caspersen found two round-off errors. Gregor Ulm sent several corrections and suggestions. Dimitrios Tsirigkas suggested I clarify an exercise. Carlos Tafur sent a page of corrections and suggestions. Martin Nordsletten found a bug in an exercise solution. Lars O.D. Christensen found a broken reference. Victor Simeone found a typo. Sven Hoexter pointed out that a variable named input shadows a build-in function. Viet Le found a typo. Stephen Gregory pointed out the problem with cmp in Python 3. Matthew Shultz let me know about a broken link. Lokesh Kumar Makani let me know about some broken links and some changes in error messages. Ishwar Bhat corrected my statement of Fermat s last theorem. Brian McGhie suggested a clarification. Andrea Zanella translated the book into Italian, and sent a number of corrections along the way.
12 xii Chapter 0. Preface
13 Contents Preface v 1 The way of the program The Python programming language What is a program? What is debugging? Formal and natural languages The first program Debugging Glossary Exercises Variables, expressions and statements Values and types Variables Variable names and keywords Operators and operands Expressions and statements Interactive mode and script mode Order of operations String operations Comments Debugging Glossary Exercises
14 xiv Contents 3 Functions Function calls Type conversion functions Math functions Composition Adding new functions Definitions and uses Flow of execution Parameters and arguments Variables and parameters are local Stack diagrams Fruitful functions and void functions Why functions? Importing with from Debugging Glossary Exercises Case study: interface design TurtleWorld Simple repetition Exercises Encapsulation Generalization Interface design Refactoring A development plan docstring Debugging Glossary Exercises
15 Contents xv 5 Conditionals and recursion Modulus operator Boolean expressions Logical operators Conditional execution Alternative execution Chained conditionals Nested conditionals Recursion Stack diagrams for recursive functions Infinite recursion Keyboard input Debugging Glossary Exercises Fruitful functions Return values Incremental development Composition Boolean functions More recursion Leap of faith One more example Checking types Debugging Glossary Exercises
16 xvi Contents 7 Iteration Multiple assignment Updating variables The while statement break Square roots Algorithms Debugging Glossary Exercises Strings A string is a sequence len Traversal with a for loop String slices Strings are immutable Searching Looping and counting String methods The in operator String comparison Debugging Glossary Exercises Case study: word play Reading word lists Exercises Search Looping with indices Debugging Glossary Exercises
17 Contents xvii 10 Lists A list is a sequence Lists are mutable Traversing a list List operations List slices List methods Map, filter and reduce Deleting elements Lists and strings Objects and values Aliasing List arguments Debugging Glossary Exercises Dictionaries Dictionary as a set of counters Looping and dictionaries Reverse lookup Dictionaries and lists Memos Global variables Long integers Debugging Glossary Exercises
18 xviii Contents 12 Tuples Tuples are immutable Tuple assignment Tuples as return values Variable-length argument tuples Lists and tuples Dictionaries and tuples Comparing tuples Sequences of sequences Debugging Glossary Exercises Case study: data structure selection Word frequency analysis Random numbers Word histogram Most common words Optional parameters Dictionary subtraction Random words Markov analysis Data structures Debugging Glossary Exercises Files Persistence Reading and writing Format operator Filenames and paths
19 Contents xix 14.5 Catching exceptions Databases Pickling Pipes Writing modules Debugging Glossary Exercises Classes and objects User-defined types Attributes Rectangles Instances as return values Objects are mutable Copying Debugging Glossary Exercises Classes and functions Time Pure functions Modifiers Prototyping versus planning Debugging Glossary Exercises
20 xx Contents 17 Classes and methods Object-oriented features Printing objects Another example A more complicated example The init method The str method Operator overloading Type-based dispatch Polymorphism Debugging Interface and implementation Glossary Exercises Inheritance Card objects Class attributes Comparing cards Decks Printing the deck Add, remove, shuffle and sort Inheritance Class diagrams Debugging Data encapsulation Glossary Exercises
21 Contents xxi 19 Case study: Tkinter GUI Buttons and callbacks Canvas widgets Coordinate sequences More widgets Packing widgets Menus and Callables Binding Debugging Glossary Exercises A Debugging 193 A.1 Syntax errors A.2 Runtime errors A.3 Semantic errors B Analysis of Algorithms 201 B.1 Order of growth B.2 Analysis of basic Python operations B.3 Analysis of search algorithms B.4 Hashtables C Lumpy 211 C.1 State diagram C.2 Stack diagram C.3 Object diagrams C.4 Function and class objects C.5 Class Diagrams
22 xxii Contents
23 Chapter 1 The way of the program The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, computer scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions. The single most important skill for a computer scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. That s why this chapter is called, The way of the program. On one level, you will be learning to program, a useful skill by itself. On another level, you will use programming as a means to an end. As we go along, that end will become clearer. 1.1 The Python programming language The programming language you will learn is Python. Python is an example of a high-level language; other high-level languages you might have heard of are C, C++, Perl, and Java. There are also low-level languages, sometimes referred to as machine languages or assembly languages. Loosely speaking, computers can only run programs written in lowlevel languages. So programs written in a high-level language have to be processed before they can run. This extra processing takes some time, which is a small disadvantage of high-level languages. The advantages are enormous. First, it is much easier to program in a high-level language. Programs written in a high-level language take less time to write, they are shorter and easier to read, and they are more likely to be correct. Second, high-level languages are portable, meaning that they can run on different kinds of computers with few or no modifications. Low-level programs can run on only one kind of computer and have to be rewritten to run on another.
Think Python Wikibooks.org March 16, 2013 On the 28th of April 2012 the contents of the English as well as German Wikibooks and Wikipedia projects were licensed under Creative Commons Attribution-ShareAlike
Computer Programming Course Details An Introduction to Computational Tools Prof. Mauro Gaspari: firstname.lastname@example.org Road map for today The skills that we would like you to acquire: to think like a computer
How to Think Like a Computer Scientist Learning with Python ii How to Think Like a Computer Scientist Learning with Python Allen Downey Jeffrey Elkner Chris Meyers Green Tea Press Wellesley, Massachusetts
How to Think Like a Computer Scientist How to Think Like a Computer Scientist: Learning with Python 2nd Edition documentation next index How to Think Like a Computer Scientist: Learning with Python 2nd
How to Think Like a Computer Scientist: Learning with Python Documentation Jeffrey Elkner, Allen B. Downey and Chris Meyers October 21, 2015 CONTENTS 1 Learning with Python 3 1.1 Copyright Notice...................................
WEEK ONE Introduction to Python Python is such a simple language to learn that we can throw away the manual and start with an example. Traditionally, the first program to write in any programming language
COMP150: Practical Programming (in Python) Jeffrey Elkner Allen B. Downey Chris Meyers Brendan McCane Iain Hewson Nick Meek June 22, 2009 ii Contents 1 The way of the program 1 1.1 The Python programming
Think Java How to Think Like a Computer Scientist Allen B. Downey 5.1.2 Copyright 2012 Allen Downey. Permission is granted to copy, distribute, transmit and adapt this work under a Creative Commons Attribution-NonCommercial-ShareAlike
How to Think Like a Computer Scientist C Version Allen B. Downey C-Version by Thomas Scheffler Version 1.08 November 25th, 2012 2 Copyright (C) 1999 Allen B. Downey This book is an Open Source Textbook
How to Think Like a Computer Scientist Java Version ii How to Think Like a Computer Scientist Java Version Allen B. Downey Version 4.0 March 6, 2003 Copyright c 2003 Allen Downey. Permission is granted
http://www.webcartoonmaker.com Copyright Information This book is an Open Source Textbook (OST). Permission is granted to reproduce, store or transmit the text of this book by any means, electrical, mechanical,
LING115 Lecture Note Session #4 Python (1) 1. Introduction As we have seen in previous sessions, we can use Linux shell commands to do simple text processing. We now know, for example, how to count words.
Introduction Welcome to our Python sessions. University of Hull Department of Computer Science Wrestling with Python Week 01 Playing with Python Vsn. 1.0 Rob Miles 2013 Please follow the instructions carefully.
River Dell Regional School District Computer Programming with Python Curriculum 2015 Mr. Patrick Fletcher Superintendent River Dell Regional Schools Ms. Lorraine Brooks Principal River Dell High School
How to think like a computer scientist Allen B. Downey November 2012 2 How to think like a computer scientist C++ Version Copyright (C) 2012 Allen B. Downey Permission is granted to copy, distribute, and/or
Welcome to Introduction to programming in Python Suffolk One, Ipswich, 4:30 to 6:00 Tuesday Jan 14, Jan 21, Jan 28, Feb 11 Welcome Fire exits Toilets Refreshments 1 Learning objectives of the course An
Exercise 4 Learning Python language fundamentals Work with numbers Python can be used as a powerful calculator. Practicing math calculations in Python will help you not only perform these tasks, but also
Domains and Competencies DOMAIN I TECHNOLOGY APPLICATIONS CORE Standards Assessed: Computer Science 8 12 I VII Competency 001: The computer science teacher knows technology terminology and concepts; the
PHP Debugging Draft: March 19, 2013 2013 Christopher Vickery Introduction Debugging is the art of locating errors in your code. There are three types of errors to deal with: 1. Syntax errors: When code
VISUAL GUIDE to RX Scripting for Roulette Xtreme - System Designer 2.0 UX Software - 2009 TABLE OF CONTENTS INTRODUCTION... ii What is this book about?... iii How to use this book... iii Time to start...
Charles Dierbach Wiley Contents Preface Acknowledgments About the Author XXI xxv xxvii Introduction 1 MOTIVATION 2 FUNDAMENTALS 2 1.1 What Is Computer Science? 2 1.1.1 The Essence of Computational Problem
Fundamentals of Java Programming This document is exclusive property of Cisco Systems, Inc. Permission is granted to print and copy this document for non-commercial distribution and exclusive use by instructors
COLLEGE ALGEBRA Paul Dawkins Table of Contents Preface... iii Outline... iv Preliminaries... Introduction... Integer Exponents... Rational Exponents... 9 Real Exponents...5 Radicals...6 Polynomials...5
Principles of Programming Languages Prof: S. Arun Kumar Department of Computer Science and Engineering Indian Institute of Technology Delhi Lecture no 7 Lecture Title: Syntactic Classes Welcome to lecture
How to Think Like a Computer Scientist How to Think Like a Computer Scientist: Learning with Python How to Think Like a Computer Scientist: Learning with Python» next index How to Think Like a Computer
Chapter 1 1.1Reasons for Studying Concepts of Programming Languages a) Increased ability to express ideas. It is widely believed that the depth at which we think is influenced by the expressive power of
Python Programming: An Introduction to Computer Science Chapter 1 Computers and Programs 1 Objectives To understand the respective roles of hardware and software in a computing system. To learn what computer
The Basics of C Programming Marshall Brain Last updated: October 30, 2013 Contents 1 C programming 1 What is C?................................. 2 The simplest C program, I........................ 2 Spacing
Object Calisthenics 9 steps to better software design today, by Jeff Bay http://www.xpteam.com/jeff/writings/objectcalisthenics.rtf http://www.pragprog.com/titles/twa/thoughtworks-anthology We ve all seen
Chapter 12 Programming Concepts and Languages Chapter 12 Programming Concepts and Languages Paradigm Publishing, Inc. 12-1 Presentation Overview Programming Concepts Problem-Solving Techniques The Evolution
Unit- I Introduction to c Language: C is a general-purpose computer programming language developed between 1969 and 1973 by Dennis Ritchie at the Bell Telephone Laboratories for use with the Unix operating
Udacity cs101: Building a Search Engine Unit 1: How to get started: your first program Extracting a Link Introducing the Web Crawler (Video: Web Crawler)... 2 Quiz (Video: First Quiz)...2 Programming (Video:
Moving from CS 61A Scheme to CS 61B Java Introduction Java is an object-oriented language. This document describes some of the differences between object-oriented programming in Scheme (which we hope you
Computer Programming I & II* Career Cluster Information Technology Course Code 10152 Prerequisite(s) Computer Applications, Introduction to Information Technology Careers (recommended), Computer Hardware
Preface This book is an introduction to computer science. It is intended for beginning CS majors or students from other fields who want a general introduction to computer science and computer programming.
Object Oriented Software Design Introduction to Java - II Giuseppe Lipari http://retis.sssup.it/~lipari Scuola Superiore Sant Anna Pisa October 28, 2010 G. Lipari (Scuola Superiore Sant Anna) Introduction
Experiences with Online Programming Examinations Monica Farrow and Peter King School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh EH14 4AS Abstract An online programming examination
s CMPS 5P (Professor Theresa Migler-VonDollen ): Assignment #8 Problem 6 Problem 1 Programming Exercises Modify the recursive Fibonacci program given in the chapter so that it prints tracing information.
Java Application Developer Certificate Program Competencies After completing the following units, you will be able to: Basic Programming Logic Explain the steps involved in the program development cycle
Extracted from: Practical Programming, 2nd Edition An Introduction to Computer Science Using Python 3 This PDF file contains pages extracted from Practical Programming, 2nd Edition, published by the Pragmatic
Problem 3 If A is divided by B the result is 2/3. If B is divided by C the result is 4/7. What is the result if A is divided by C? Suggested Questions to ask students about Problem 3 The key to this question
[Mechanical Translation, vol.5, no.1, July 1958; pp. 25-41] A Programming Language for Mechanical Translation Victor H. Yngve, Massachusetts Institute of Technology, Cambridge, Massachusetts A notational
Chapter 2 Writing Simple Programs Objectives To know the steps in an orderly software development process. To understand programs following the Input, Process, Output (IPO) pattern and be able to modify
LEARNING TO PROGRAM WITH PYTHON Richard L. Halterman Copyright 2011 Richard L. Halterman. All rights reserved. i Contents 1 The Context of Software Development 1 1.1 Software............................................
CSCE 110 Programming Basics of Python: Variables, Expressions, and nput/output Dr. Tiffani L. Williams Department of Computer Science and Engineering Texas A&M University Fall 2011 Python Python was developed
Chapter 1 CS-4337 Organization of Programming Languages Dr. Chris Irwin Davis Email: email@example.com Phone: (972) 883-3574 Office: ECSS 4.705 Chapter 1 Topics Reasons for Studying Concepts of Programming
Object Oriented Software Design Introduction to Java - II Giuseppe Lipari http://retis.sssup.it/~lipari Scuola Superiore Sant Anna Pisa September 14, 2011 G. Lipari (Scuola Superiore Sant Anna) Introduction
Computer Science 217 Midterm Exam Fall 2009 October 29, 2009 Name: ID: Instructions: Neatly print your name and ID number in the spaces provided above. Pick the best answer for each multiple choice question.
Thomas Jefferson High School for Science and Technology Program of Studies Accelerated Foundations of Computer Science as of April 2013 Unit of Study / Accelerated Foundations of Computer Science is offered
What to Expect on the Compass What is the Compass? COMPASS is a set of untimed computer adaptive tests created by the American College Test (ACT) Program. Because COMPASS tests are "computer adaptive,"
Introduction to Programming and Algorithms Module 1 CS 146 Sam Houston State University Dr. Tim McGuire Module Objectives To understand: the necessity of programming, differences between hardware and software,
Understanding Computers Today and Tomorrow 12 th Edition Chapter 13: Program Development and Programming Languages Learning Objectives Understand the differences between structured programming, object-oriented
Performance Assessment Task Quadratic (2009) Grade 9 The task challenges a student to demonstrate an understanding of quadratic functions in various forms. A student must make sense of the meaning of relations
Python Programming: An Introduction to Computer Science Chapter 1 Computers and Programs Objectives Introduction to the class Why we program and what that means Introduction to the Python programming language
Python Programming: An Introduction to Computer Science Chapter 1 Computers and Programs 1 The Universal Machine n A computer -- a machine that stores and manipulates information under the control of a
PGR Computing Programming Skills Dr. I. Hawke 2008 1 Introduction The purpose of computing is to do something faster, more efficiently and more reliably than you could as a human do it. One obvious point
CS 40 Computing for the Web Art Lee January 20, 2015 Announcements Course web on Sakai Homework assignments submit them on Sakai Email me the survey: See the Announcements page on the course web for instructions
PROBLEM SOLVING WITH SEVENTH EDITION WALTER SAVITCH UNIVERSITY OF CALIFORNIA, SAN DIEGO CONTRIBUTOR KENRICK MOCK UNIVERSITY OF ALASKA, ANCHORAGE PEARSON Addison Wesley Boston San Francisco New York London
Pseudo code Tutorial and Exercises Teacher s Version Pseudo-code is an informal way to express the design of a computer program or an algorithm in 1.45. The aim is to get the idea quickly and also easy
CS 106 Introduction to Computer Science I 01 / 21 / 2014 Instructor: Michael Eckmann Today s Topics Introduction Homework assignment Review the syllabus Review the policies on academic dishonesty and improper
SOFTWARE DEVELOPMENT, 15.1200.40 1.0 APPLY PROBLEM-SOLVING AND CRITICAL THINKING SKILLS TO INFORMATION TECHNOLOGY 1.1 Describe methods and considerations for prioritizing and scheduling software development
Tips for Solving Mathematical Problems Don Byrd Revised late April 2011 The tips below are based primarily on my experience teaching precalculus to high-school students, and to a lesser extent on my other
Caltech/LEAD Summer 2012 Computer Science Lecture 2: July 10, 2012 Introduction to Python The Python shell Outline Python as a calculator Arithmetic expressions Operator precedence Variables and assignment
Python Programming: An Introduction To Computer Science Chapter 8 Booleans and Control Structures Python Programming, 2/e 1 Objectives æ To understand the concept of Boolean expressions and the bool data
Parsing Technology and its role in Legacy Modernization A Metaware White Paper 1 INTRODUCTION In the two last decades there has been an explosion of interest in software tools that can automate key tasks
WEEK THREE Python Lists and Loops You ve made it to Week 3, well done! Most programs need to keep track of a list (or collection) of things (e.g. names) at one time or another, and this week we ll show
Chapter 3 Input and output The programs we ve looked at so far just display messages, which doesn t involve a lot of real computation. This chapter will show you how to read input from the keyboard, use
A Concrete Introduction to the Abstract Concepts of Integers and Algebra using Algebra Tiles Table of Contents Introduction... 1 page Integers 1: Introduction to Integers... 3 2: Working with Algebra Tiles...
CHAPTER 3 Numbers and Numeral Systems Numbers play an important role in almost all areas of mathematics, not least in calculus. Virtually all calculus books contain a thorough description of the natural,
Lecture 9. Semantic Analysis Scoping and Symbol Table Wei Le 2015.10 Outline Semantic analysis Scoping The Role of Symbol Table Implementing a Symbol Table Semantic Analysis Parser builds abstract syntax
Balanced Assessment Test Algebra 2008 Core Idea Task Score Representations Expressions This task asks students find algebraic expressions for area and perimeter of parallelograms and trapezoids. Successful
Java 6 'th edition Concepts INTERNATIONAL STUDENT VERSION CONTENTS PREFACE vii SPECIAL FEATURES xxviii chapter i INTRODUCTION 1 1.1 What Is Programming? 2 J.2 The Anatomy of a Computer 3 1.3 Translating
Chapter Four: How to Collaborate and Write With Others Why Collaborate on Writing? Considering (and Balancing) the Two Extremes of Collaboration Peer Review as Collaboration * A sample recipe for how peer
Random Fibonacci-type Sequences in Online Gambling Adam Biello, CJ Cacciatore, Logan Thomas Department of Mathematics CSUMS Advisor: Alfa Heryudono Department of Mathematics University of Massachusetts
Appendix E Glossary of Object Oriented Terms abstract class: A class primarily intended to define an instance, but can not be instantiated without additional methods. abstract data type: An abstraction
Hypercosm Studio www.hypercosm.com Hypercosm Studio Guide 3 Revision: November 2005 Copyright 2005 Hypercosm LLC All rights reserved. Hypercosm, OMAR, Hypercosm 3D Player, and Hypercosm Studio are trademarks
Programming and Software Development CTAG Alignments This document contains information about four Career-Technical Articulation Numbers (CTANs) for Programming and Software Development Career-Technical
Python Programming: An Introduction to Computer Science Sequences: Strings and Lists Python Programming, 2/e 1 Objectives To understand the string data type and how strings are represented in the computer.
CS101 Lecture 24: Thinking in Python: Input and Output Variables and Arithmetic Aaron Stevens 28 March 2011 1 Overview/Questions Review: Programmability Why learn programming? What is a programming language?
Chapter One Introduction to Programming 1-1 Algorithm and Flowchart Algorithm is a step-by-step procedure for calculation. More precisely, algorithm is an effective method expressed as a finite list of