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The CS Detective: An Algorithmic Tale of Crime, Conspiracy, and Computation PDF

259 Pages·2016·7.94 MB·English
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T HE j e r e m y k u b i c a C S D E T E C T I V E S C E H T E V I T C E T • The algorithms behind best-first and depth-first search, iterative E D deepening, parallelizing, binary search, and more • Basic computational concepts like strings, arrays, stacks, and queues •• HTtoho ewa pm tpool ysa tcd oeamfpftimc sioeenna-trs caehln gasolerg iohthreimuthrsims ttsoi c tu oms eue ntinhu osadu gsailv deant asi tsutrautciotnu,r easnd when ACnToa nAlsepCl oigormofarp ciutCythr,a imtamiineocd ,n The CS Detective THE CS DETECTIVE An Algorithmic Tale of Crime, Conspiracy, and Computation jeremy kubica SAn FrAnCiSCo The CS DeTeCTive. Copyright © 2016 by Jeremy Kubica. All rights reserved. No part of this work may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage or retrieval system, without the prior written permission of the copyright owner and the publisher. Printed in USA First printing 20 19 18 17 16 1 2 3 4 5 6 7 8 9 ISBN-10: 1-59327-749-0 ISBN-13: 978-1-59327-749-9 Publisher: William Pollock Production Editor: Riley Hoffman Cover and Interior Design: Beth Middleworth Illustrator: Miran Lipovac� a Developmental Editor: Liz Chadwick Technical Reviewer: Heidi Newton Copyeditor: Rachel Monaghan Compositor: Riley Hoffman Proofreader: Paula L. Fleming For information on distribution, translations, or bulk sales, please contact No Starch Press, Inc. directly: No Starch Press, Inc. 245 8th Street, San Francisco, CA 94103 phone: 415.863.9900; [email protected] www.nostarch.com Library of Congress Cataloging-in-Publication Data Names: Kubica, Jeremy. Title: The CS detective : an algorithmic tale of crime, conspiracy, and computation / by Jeremy Kubica. Description: San Francisco : No Starch Press, [2016] | Summary: “A mystery novel for computer science students and enthusiasts that introduces the concepts behind search algorithms and data structures. Each chapter teaches a new concept, ending with a technical explanation.”-- Provided by publisher. Identifiers: LCCN 2016013632 (print) | LCCN 2016026435 (ebook) | ISBN 9781593277499 (pbk.) | ISBN 1593277490 (pbk.) | ISBN 9781593277871 (epub) | ISBN 1593277873 (epub) | ISBN 9781593277888 (mobi) | ISBN 1593277881 (mobi) Subjects: | CYAC: Algorithms--Fiction. | Computer science--Fiction. | Mystery and detective stories. Classification: LCC PZ7.1.K8 Cs 2016 (print) | LCC PZ7.1.K8 (ebook) | DDC [Fic]--dc23 LC record available at https://lccn.loc.gov/2016013632 No Starch Press and the No Starch Press logo are registered trademarks of No Starch Press, Inc. Other product and company names mentioned herein may be the trademarks of their respective owners. Rather than use a trademark symbol with every occurrence of a trademarked name, we are using the names only in an editorial fashion and to the benefit of the trademark owner, with no inten- tion of infringement of the trademark. The information in this book is distributed on an “As Is” basis, without warranty. While every pre- caution has been taken in the preparation of this work, neither the author nor No Starch Press, Inc. shall have any liability to any person or entity with respect to any loss or damage caused or alleged to be caused directly or indirectly by the information contained in it. All characters in this publication are fictitious, and any resemblance to real persons, living or dead, is purely coincidental. about the author Jeremy Kubica is a principal engineer at Google working on machine learning and algorithms. He has a PhD in robotics from Carnegie Mellon University and a BS in computer science from Cornell University. He spent his graduate school years creating algorithms to detect killer asteroids (actually stopping them was, of course, left as “future work”). Kubica is the author of the popular Computational Fairy Tales blog. about the technical reviewer Heidi Newton has a BSc from the University of Canterbury, New Zealand, and an MSc from Victoria University of Wellington, New Zealand, both in computer science. She works for the University of Canterbury’s computer science education research group and Code Avengers, and on the side carries out related tutoring and consul- tancy work. Her current focus is on improving teaching resources for computer science and programming. contents Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .ix A Note to Readers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xi chapter 1 Search Problems. . . . . . . . . . . . . . . . . . . . . . . . . . .1 chapter 2 Exhaustive Search for an Informant. . . . . . . . . . .9 chapter 3 Arrays and Indexes on a Criminal’s Farm . . . . .17 chapter 4 Strings and Hidden Messages. . . . . . . . . . . . . . .25 chapter 5 Binary Search for a Smuggler’s Ship . . . . . . . . .29 chapter 6 Binary Search for Clues. . . . . . . . . . . . . . . . . . . .39 chapter 7 Adapting Algorithms for a Daring Escape . . . . .47 chapter 8 Socks: An Interlude and an Introduction . . . . . .57 chapter 9 Backtracking to Keep the Search Going. . . . . . .65 chapter 10 Picking Locks with Breadth-First Search. . . . . .71 chapter 11 Depth-First Search in an Abandoned Prison . . .83 chapter 12 Cafeteria Stacks and Queues. . . . . . . . . . . . . . . .93 chapter 13 Stacks and Queues for Search. . . . . . . . . . . . . .103 chapter 14 Let’s Split Up: Parallelized Search . . . . . . . . . .109 chapter 15 Iterative Deepening Can Save Your Life . . . . .117 chapter 16 Inverted Indexes: The Search Narrows. . . . . . .127 chapter 17 A Binary Search Tree Trap . . . . . . . . . . . . . . . .135 chapter 18 Building Binary Search Ladders. . . . . . . . . . . .145 chapter 19 Binary Search Trees for Suspects . . . . . . . . . . .151 chapter 20 Adding Suspects to the Search Tree . . . . . . . . .163 chapter 21 The Binary Search Tree Property. . . . . . . . . . .171 chapter 22 Tries for Paperwork . . . . . . . . . . . . . . . . . . . . . .175 chapter 23 Best-First Search: A Detective’s Most Trusted Tool . . . . . . . . . . . . . . . . . . . . . . .183 chapter 24 Priority Queues for Investigations . . . . . . . . . .193 chapter 25 Priority Queues for Lock Picking . . . . . . . . . . .201 chapter 26 Heuristics in Search. . . . . . . . . . . . . . . . . . . . . .207 chapter 27 Heaps in Politics and Academia . . . . . . . . . . . .213 chapter 28 Difficult Search Problems . . . . . . . . . . . . . . . . .223 chapter 29 Search Termination . . . . . . . . . . . . . . . . . . . . . .231 Epilogue. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .237 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .239 viii CONTENTS

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Meet Frank Runtime. Disgraced ex-detective. Hard-boiled private eye. Search expert.When a robbery hits police headquarters, it’s up to Frank Runtime and his extensive search skills to catch the culprits. In this detective story, you’ll learn how to use algorithmic tools to solve the case. Runtim
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