1. (15 points) (a) How many bit strings of length 8 are there? Explain. (b) How many bit strings of length 8 are there which begin with a 0 and end with a 0? Explain. (c) How many bit strings of length 8 are there which contain at most 3 ones? Be careful with this one. Explain. (See your notes, week 10.) (d) How many bit strings of length 8 are palindromes? 3. (10 points) (a) Text, page 405, number 2. Explain. (b) Text, page 406, number 36. Explain 3. (10 points). Text, page 414, number 30. Explain. 4. (10 points) (a) Use the Binomial Theorem to write the expansion of (x + y) 6? (b) Write the coefficient of the term x2y4z5 expansion of (x + y + z) 11. See example 12 in your notes of week 10 5. Study pages 1-4 of the notes for week 11. Let A = {a, b, c, d}, and let R be the relation defined on A by the following matrix: 1 0 1 0  0 1 1 0   MR =  0 0 1 1    1 1 0 1  (a) (10 pts.) Describe R by listing the ordered pairs in R and draw the digraph of this relation. (b) (15 pts.) (Note this is similar to exercise 7 page 630. Which of the properties: reflexive, antisymmetric and transitive are true for the given relation? Begin your discussion by defining each term in general first and then how the definition relates to this specific example. (c) (5 pts.) Is this relation a partial order? Explain. If this relation is a partial order, draw its Hasse diagram. 6. (10 points) Use the Hasse diagram of number 26 page 631 (a) List the ordered pairs that belong to the relation. Keep in mind that a Hasse diagram is a graph of a partial ordering relation so it satisfies the three properties listed in number 5 part (b). (b) Find the (Boolean) matrix of the relation. 7. (15 points) Before you do this problem study the example at the end of the exam, as well as the notes in weeks 12 and 13. Assume the Boolean matrix below is MR and that MR represents the relation R where R represents the connecting flights that an airline has between 4 cities: a, b, c, and d. The 1 in row a column b means there is a flight from city a (Manchester) to city b (Boston). The 1 in row x column x means that there are planes in airport x. In general, there is a 1 in row x column y iff there is a connecting flight between (from) city x and (to) city y That is, the rows of the matrix represent the cities of the origins of the flights and the columns represent the destination cities. a b c d a 1 Let MR = b 1  c 1  d 0 1 1 0 0 0 1 1 1 1 0  0  1 (i) Let a stand for the airport in the city of Manchester, let b stand for the airport in Boston, c stand for the Chicago airport, d for the airport in the city of Denver. Is their a flight from Denver to Chicago? Explain. (ii) Compute and interpret the Boolean products: MR 2, and MR 3. (Remember to use Boolean arithmetic). What do these Boolean products give you? That is, explain what the Boolean entries in the matrices MR 2 and MR 3 mean. (iii) Now call the given matrix A and compute A2 and A3 , using regular, not Boolean arithmetic. What do these products give you? (v) What does MR + M2R + M3R + M4R give you? Note, this is Theorem 3 page 602where the text’s symbol, v, for Boolean addition is replaced by +, another symbol for Boolean addition . Questions that test your knowledge 1. Make up a question using the idea of question 7 (Something you do at work, home, something you’re interested in.) See 3 below for an example you can do. 2. In your notes of week 12 Project Evaluation and Review Technique (PERT) is explained. Make up a meaningful example illustrating this process. Explain all details. Draw the graphs involved. You should use a reasonable number of tasks. (a) Determine the minimum time needed to complete your set of tasks. (b) Determine the Critical Path for your example. Explain what this gives you. (c) Comment on your example. Which task(s) cause a delay in the project? How would you fix the problem? Can you obtain more information out of your example? 3. The Network analysis problem. 4. Read Program Evaluation and Review Technique (PERT) in your week 14 notes. Note the examples given here are a little “ambitious”. Make up an example using PERT and find and explain the critical path of your example. Google “critical path analysis”, for more ideas. 5. Pg 406 #38 If #7 is not clear here is an example which may help you to understand #7 Let D = days of the week {M, T, W, R, F}, E = {Brian (B), Jim (J), Karen (K)} be the employees of a tutoring center at a University and let U = {Courses the tutoring center needs tutors for} = {Calculus I (I), Calculus II (II), Calculus III (III), Computers I (C1), Computers II (C2), Precalculus (P)}. We define the relation R from D into E by d R e, if employee e is scheduled to work on day d. We also define S from E into U by e r u, if employee e is capable of tutoring students in course u. For example, the matrix MR indicates that on R (Thursday) that J (Jim) is available to tutor but Brian and Karen are not. B J K M 1 T 0 Assume MR = W 1  R 0 F 1 0 1 0 1 1 I 1  1 B 0 and MS =  1 J 1  0 K 0 0  II III C1 C2 P 1 1 1 1 0 0 0 1 0 0 1 0 1  1 1 (a) Interpret the above matrices with respect to the above relations. (b) Compute MS R , (use Boolean arithmetic) and use the matrix MS R to determine which courses will have tutors available on which days. (c) Multiply the above matrices using regular arithmetic. Can you interpret this result? The Leading Text in Discrete Mathematics The seventh edition of Kenneth Rosen’s Discrete Mathematics and Its Applications is a substantial revision of the most widely used textbook in its field. This new edition reflects extensive feedback from instructors, students, and more than 50 reviewers. It also reflects the insights of the author based on his experience in industry and academia. Key benefits of this edition are: Rosen Discrete Mathematics and Its Applications Kenneth H. Rosen SEVENTH EDITION MD DALIM 1145224 05/14/11 CYAN MAG YELO BLACK Discrete Mathematics and Its Applications Discrete Mathematics and Its Applications SEVENTH EDITION TM P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Discrete Mathematics and Its Applications Seventh Edition Kenneth H. Rosen Monmouth University (and formerly AT&T Laboratories) i P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 DISCRETE MATHEMATICS AND ITS APPLICATIONS, SEVENTH EDITION Published by McGraw-Hill, a business unit of The McGraw-Hill Companies, Inc., 1221 Avenue of the Americas, New York, NY 10020. Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved. Previous editions © 2007, 2003, and 1999. No part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written consent of The McGraw-Hill Companies, Inc., including, but not limited to, in any network or other electronic storage or transmission, or broadcast for distance learning. Some ancillaries, including electronic and print components, may not be available to customers outside the United States. This book is printed on acid-free paper. 1 2 3 4 5 6 7 8 9 0 DOW/DOW 1 0 9 8 7 6 5 4 3 2 1 ISBN 978-0-07-338309-5 MHID 0-07-338309-0 Vice President & Editor-in-Chief: Marty Lange Editorial Director: Michael Lange Global Publisher: Raghothaman Srinivasan Executive Editor: Bill Stenquist Development Editors: Lorraine K. Buczek/Rose Kernan Senior Marketing Manager: Curt Reynolds Project Manager: Robin A. Reed Buyer: Sandy Ludovissy Design Coordinator: Brenda A. Rolwes Cover painting: Jasper Johns, Between the Clock and the Bed, 1981. Oil on Canvas (72 × 126 1/4 inches) Collection of the artist. Photograph by Glenn Stiegelman. Cover Art © Jasper Johns/Licensed by VAGA, New York, NY Cover Designer: Studio Montage, St. Louis, Missouri Lead Photo Research Coordinator: Carrie K. Burger Media Project Manager: Tammy Juran Production Services/Compositor: RPK Editorial Services/PreTeX, Inc. Typeface: 10.5/12 Times Roman Printer: R.R. Donnelley All credits appearing on this page or at the end of the book are considered to be an extension of the copyright page. Library of Congress Cataloging-in-Publication Data Rosen, Kenneth H. Discrete mathematics and its applications / Kenneth H. Rosen. — 7th ed. p. cm. Includes index. ISBN 0–07–338309–0 1. Mathematics. 2. Computer science—Mathematics. I. Title. QA39.3.R67 2012 511–dc22 2011011060 www.mhhe.com ii P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Contents About the Author vi Preface vii The Companion Website xvi To the Student xvii 1 The Foundations: Logic and Proofs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 Propositional Logic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Applications of Propositional Logic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Propositional Equivalences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Predicates and Quantifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Nested Quantifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Rules of Inference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Introduction to Proofs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Proof Methods and Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 2 Basic Structures: Sets, Functions, Sequences, Sums, and Matrices . 115 2.1 2.2 2.3 2.4 2.5 2.6 Sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Set Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 Sequences and Summations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 Cardinality of Sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 Matrices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 3 Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 3.1 3.2 3.3 Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 The Growth of Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 Complexity of Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232 4 Number Theory and Cryptography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 4.1 4.2 4.3 4.4 4.5 4.6 Divisibility and Modular Arithmetic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 Integer Representations and Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Primes and Greatest Common Divisors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257 Solving Congruences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274 Applications of Congruences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287 Cryptography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306 iii P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T iv T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Contents 5 Induction and Recursion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 5.1 5.2 5.3 5.4 5.5 Mathematical Induction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Strong Induction and Well-Ordering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 Recursive Definitions and Structural Induction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344 Recursive Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360 Program Correctness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 372 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 6 Counting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385 6.1 6.2 6.3 6.4 6.5 6.6 The Basics of Counting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385 The Pigeonhole Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 Permutations and Combinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 Binomial Coefficients and Identities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415 Generalized Permutations and Combinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 423 Generating Permutations and Combinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 434 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439 7 Discrete Probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445 7.1 7.2 7.3 7.4 An Introduction to Discrete Probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445 Probability Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 452 Bayes’ Theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 468 Expected Value and Variance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 494 8 Advanced Counting Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501 8.1 8.2 8.3 8.4 8.5 8.6 Applications of Recurrence Relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501 Solving Linear Recurrence Relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514 Divide-and-Conquer Algorithms and Recurrence Relations . . . . . . . . . . . . . . . . . . . . . . . 527 Generating Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 537 Inclusion–Exclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 552 Applications of Inclusion–Exclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 565 9 Relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 573 9.1 9.2 9.3 9.4 9.5 9.6 Relations and Their Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 573 n-ary Relations and Their Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 583 Representing Relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591 Closures of Relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 597 Equivalence Relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 607 Partial Orderings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 618 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633 P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Contents v 10 Graphs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 641 10.1 10.2 10.3 10.4 10.5 10.6 10.7 10.8 Graphs and Graph Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 641 Graph Terminology and Special Types of Graphs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 651 Representing Graphs and Graph Isomorphism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 668 Connectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 678 Euler and Hamilton Paths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 693 Shortest-Path Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 707 Planar Graphs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 718 Graph Coloring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 727 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 735 11 Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 745 11.1 11.2 11.3 11.4 11.5 Introduction to Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 745 Applications of Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 757 Tree Traversal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 772 Spanning Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 785 Minimum Spanning Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 797 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 803 12 Boolean Algebra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 811 12.1 12.2 12.3 12.4 Boolean Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 811 Representing Boolean Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 819 Logic Gates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 822 Minimization of Circuits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 828 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 843 13 Modeling Computation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 847 13.1 13.2 13.3 13.4 13.5 Languages and Grammars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 847 Finite-State Machines with Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 858 Finite-State Machines with No Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 865 Language Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 878 Turing Machines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 888 End-of-Chapter Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 899 Appendixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-1 1 2 3 Axioms for the Real Numbers and the Positive Integers . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Exponential and Logarithmic Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Pseudocode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Suggested Readings B-1 Answers to Odd-Numbered Exercises S-1 Photo Credits C-1 Index of Biographies I-1 Index I-2 P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 About the Author K enneth H. Rosen has had a long career as a Distinguished Member of the Technical Staff at AT&T Laboratories in Monmouth County, New Jersey. He currently holds the position of Visiting Research Professor at Monmouth University, where he teaches graduate courses in computer science. Dr. Rosen received his B.S. in Mathematics from the University of Michigan, Ann Arbor (1972), and his Ph.D. in Mathematics from M.I.T. (1976), where he wrote his thesis in the area of number theory under the direction of Harold Stark. Before joining Bell Laboratories in 1982, he held positions at the University of Colorado, Boulder; The Ohio State University, Columbus; and the University of Maine, Orono, where he was an associate professor of mathematics. While working at AT&T Labs, he taught at Monmouth University, teaching courses in discrete mathematics, coding theory, and data security. He currently teaches courses in algorithm design and in computer security and cryptography. Dr. Rosen has published numerous articles in professional journals in number theory and in mathematical modeling. He is the author of the widely used Elementary Number Theory and Its Applications, published by Pearson, currently in its sixth edition, which has been translated into Chinese. He is also the author of Discrete Mathematics and Its Applications, published by McGraw-Hill, currently in its seventh edition. Discrete Mathematics and Its Applications has sold more than 350,000 copies in North America during its lifetime, and hundreds of thousands of copies throughout the rest of the world. This book has also been translated into Spanish, French, Greek, Chinese, Vietnamese, and Korean. He is also co-author of UNIX: The Complete Reference; UNIX System V Release 4: An Introduction; and Best UNIX Tips Ever, all published by Osborne McGraw-Hill. These books have sold more than 150,000 copies, with translations into Chinese, German, Spanish, and Italian. Dr. Rosen is also the editor of the Handbook of Discrete and Combinatorial Mathematics, published by CRC Press, and he is the advisory editor of the CRC series of books in discrete mathematics, consisting of more than 55 volumes on different aspects of discrete mathematics, most of which are introduced in this book. Dr. Rosen serves as an Associate Editor for the journal Discrete Mathematics, where he works with submitted papers in several areas of discrete mathematics, including graph theory, enumeration, and number theory. He is also interested in integrating mathematical software into the educational and professional environments, and worked on several projects with Waterloo Maple Inc.’s MapleTM software in both these areas. Dr. Rosen has also worked with several publishing companies on their homework delivery platforms. At Bell Laboratories and AT&T Laboratories, Dr. Rosen worked on a wide range of projects, including operations research studies, product line planning for computers and data communications equipment, and technology assessment. He helped plan AT&T’s products and services in the area of multimedia, including video communications, speech recognition, speech synthesis, and image networking. He evaluated new technology for use by AT&T and did standards work in the area of image networking. He also invented many new services, and holds more than 55 patents. One of his more interesting projects involved helping evaluate technology for the AT&T attraction that was part of EPCOT Center. vi P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Preface I n writing this book, I was guided by my long-standing experience and interest in teaching discrete mathematics. For the student, my purpose was to present material in a precise, readable manner, with the concepts and techniques of discrete mathematics clearly presented and demonstrated. My goal was to show the relevance and practicality of discrete mathematics to students, who are often skeptical. I wanted to give students studying computer science all of the mathematical foundations they need for their future studies. I wanted to give mathematics students an understanding of important mathematical concepts together with a sense of why these concepts are important for applications. And most importantly, I wanted to accomplish these goals without watering down the material. For the instructor, my purpose was to design a flexible, comprehensive teaching tool using proven pedagogical techniques in mathematics. I wanted to provide instructors with a package of materials that they could use to teach discrete mathematics effectively and efficiently in the most appropriate manner for their particular set of students. I hope that I have achieved these goals. I have been extremely gratified by the tremendous success of this text. The many improvements in the seventh edition have been made possible by the feedback and suggestions of a large number of instructors and students at many of the more than 600 North American schools, and at any many universities in parts of the world, where this book has been successfully used. This text is designed for a one- or two-term introductory discrete mathematics course taken by students in a wide variety of majors, including mathematics, computer science, and engineering. College algebra is the only explicit prerequisite, although a certain degree of mathematical maturity is needed to study discrete mathematics in a meaningful way. This book has been designed to meet the needs of almost all types of introductory discrete mathematics courses. It is highly flexible and extremely comprehensive. The book is designed not only to be a successful textbook, but also to serve as valuable resource students can consult throughout their studies and professional life. Goals of a Discrete Mathematics Course A discrete mathematics course has more than one purpose. Students should learn a particular set of mathematical facts and how to apply them; more importantly, such a course should teach students how to think logically and mathematically. To achieve these goals, this text stresses mathematical reasoning and the different ways problems are solved. Five important themes are interwoven in this text: mathematical reasoning, combinatorial analysis, discrete structures, algorithmic thinking, and applications and modeling. A successful discrete mathematics course should carefully blend and balance all five themes. 1. Mathematical Reasoning: Students must understand mathematical reasoning in order to read, comprehend, and construct mathematical arguments. This text starts with a discussion of mathematical logic, which serves as the foundation for the subsequent discussions of methods of proof. Both the science and the art of constructing proofs are addressed. The technique of mathematical induction is stressed through many different types of examples of such proofs and a careful explanation of why mathematical induction is a valid proof technique. vii P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T viii T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Preface 2. Combinatorial Analysis: An important problem-solving skill is the ability to count or enumerate objects. The discussion of enumeration in this book begins with the basic techniques of counting. The stress is on performing combinatorial analysis to solve counting problems and analyze algorithms, not on applying formulae. 3. Discrete Structures: A course in discrete mathematics should teach students how to work with discrete structures, which are the abstract mathematical structures used to represent discrete objects and relationships between these objects. These discrete structures include sets, permutations, relations, graphs, trees, and finite-state machines. 4. Algorithmic Thinking: Certain classes of problems are solved by the specification of an algorithm. After an algorithm has been described, a computer program can be constructed implementing it. The mathematical portions of this activity, which include the specification of the algorithm, the verification that it works properly, and the analysis of the computer memory and time required to perform it, are all covered in this text. Algorithms are described using both English and an easily understood form of pseudocode. 5. Applications and Modeling: Discrete mathematics has applications to almost every conceivable area of study. There are many applications to computer science and data networking in this text, as well as applications to such diverse areas as chemistry, biology, linguistics, geography, business, and the Internet. These applications are natural and important uses of discrete mathematics and are not contrived. Modeling with discrete mathematics is an extremely important problem-solving skill, which students have the opportunity to develop by constructing their own models in some of the exercises. Changes in the Seventh Edition Although the sixth edition has been an extremely effective text, many instructors, including longtime users, have requested changes designed to make this book more effective. I have devoted a significant amount of time and energy to satisfy their requests and I have worked hard to find my own ways to make the book more effective and more compelling to students. The seventh edition is a major revision, with changes based on input from more than 40 formal reviewers, feedback from students and instructors, and author insights. The result is a new edition that offers an improved organization of topics making the book a more effective teaching tool. Substantial enhancements to the material devoted to logic, algorithms, number theory, and graph theory make this book more flexible and comprehensive. Numerous changes in the seventh edition have been designed to help students more easily learn the material. Additional explanations and examples have been added to clarify material where students often have difficulty. New exercises, both routine and challenging, have been added. Highly relevant applications, including many related to the Internet, to computer science, and to mathematical biology, have been added. The companion website has benefited from extensive development activity and now provides tools students can use to master key concepts and explore the world of discrete mathematics, and many new tools under development will be released in the year following publication of this book. I hope that instructors will closely examine this new edition to discover how it might meet their needs. Although it is impractical to list all the changes in this edition, a brief list that highlights some key changes, listed by the benefits they provide, may be useful. More Flexible Organization  Applications of propositional logic are found in a new dedicated section, which briefly introduces logic circuits.  Recurrence relations are now covered in Chapter 2.  Expanded coverage of countability is now found in a dedicated section in Chapter 2. P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Preface ix  Separate chapters now provide expanded coverage of algorithms (Chapter 3) and number theory and cryptography (Chapter 4).  More second and third level heads have been used to break sections into smaller coherent parts. Tools for Easier Learning  Difficult discussions and proofs have been marked with the famous Bourbaki “dangerous bend” symbol in the margin.  New marginal notes make connections, add interesting notes, and provide advice to students.  More details and added explanations, in both proofs and exposition, make it easier for students to read the book.  Many new exercises, both routine and challenging, have been added, while many existing exercises have been improved. Enhanced Coverage of Logic, Sets, and Proof  The satisfiability problem is addressed in greater depth, with Sudoku modeled in terms of satisfiability.  Hilbert’s Grand Hotel is used to help explain uncountability.  Proofs throughout the book have been made more accessible by adding steps and reasons behind these steps.  A template for proofs by mathematical induction has been added.  The step that applies the inductive hypothesis in mathematical induction proof is now explicitly noted. Algorithms  The pseudocode used in the book has been updated.  Explicit coverage of algorithmic paradigms, including brute force, greedy algorithms, and dynamic programing, is now provided.  Useful rules for big-O estimates of logarithms, powers, and exponential functions have been added. Number Theory and Cryptography  Expanded coverage allows instructors to include just a little or a lot of number theory in their courses.  The relationship between the mod function and congruences has been explained more fully.  The sieve of Eratosthenes is now introduced earlier in the book.  Linear congruences and modular inverses are now covered in more detail.  Applications of number theory, including check digits and hash functions, are covered in great depth.  A new section on cryptography integrates previous coverage, and the notion of a cryptosystem has been introduced.  Cryptographic protocols, including digital signatures and key sharing, are now covered. P1: 1/1 P2: 1/2 FRONT-7T QC: 1/1 Rosen-2311T x T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Preface Graph Theory  A structured introduction to graph theory applications has been added.  More coverage has been devoted to the notion of social networks.  Applications to the biological sciences and motivating applications for graph isomorphism and planarity have been added.  Matchings in bipartite graphs are now covered, including Hall’s theorem and its proof.  Coverage of vertex connectivity, edge connectivity, and n-connectedness has been added, providing more insight into the connectedness of graphs. Enrichment Material  Many biographies have been expanded and updated, and new biographies of Bellman, Bézout Bienyamé, Cardano, Catalan, Cocks, Cook, Dirac, Hall, Hilbert, Ore, and Tao have been added.  Historical information has been added throughout the text.  Numerous updates for latest discoveries have been made. Expanded Media  Extensive effort has been devoted to producing valuable web resources for this book.  Extra examples in key parts of the text have been provided on companion website.  Interactive algorithms have been developed, with tools for using them to explore topics and for classroom use.  A new online ancillary, The Virtual Discrete Mathematics Tutor, available in fall 2012, will help students overcome problems learning discrete mathematics.  A new homework delivery system, available in fall 2012, will provide automated homework for both numerical and conceptual exercises.  Student assessment modules are available for key concepts.  Powerpoint transparencies for instructor use have been developed.  A supplement Exploring Discrete Mathematics has been developed, providing extensive support for using MapleTM or MathematicaTM in conjunction with the book.  An extensive collection of external web links is provided. Features of the Book ACCESSIBILITY This text has proved to be easily read and understood by beginning students. There are no mathematical prerequisites beyond college algebra for almost all the content of the text. Students needing extra help will find tools on the companion website for bringing their mathematical maturity up to the level of the text. The few places in the book where calculus is referred to are explicitly noted. Most students should easily understand the pseudocode used in the text to express algorithms, regardless of whether they have formally studied programming languages. There is no formal computer science prerequisite. Each chapter begins at an easily understood and accessible level. Once basic mathematical concepts have been carefully developed, more difficult material and applications to other areas of study are presented. P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Preface xi FLEXIBILITY This text has been carefully designed for flexible use. The dependence of chapters on previous material has been minimized. Each chapter is divided into sections of approximately the same length, and each section is divided into subsections that form natural blocks of material for teaching. Instructors can easily pace their lectures using these blocks. WRITING STYLE The writing style in this book is direct and pragmatic. Precise mathematical language is used without excessive formalism and abstraction. Care has been taken to balance the mix of notation and words in mathematical statements. MATHEMATICAL RIGOR AND PRECISION All definitions and theorems in this text are stated extremely carefully so that students will appreciate the precision of language and rigor needed in mathematics. Proofs are motivated and developed slowly; their steps are all carefully justified. The axioms used in proofs and the basic properties that follow from them are explicitly described in an appendix, giving students a clear idea of what they can assume in a proof. Recursive definitions are explained and used extensively. WORKED EXAMPLES Over 800 examples are used to illustrate concepts, relate different topics, and introduce applications. In most examples, a question is first posed, then its solution is presented with the appropriate amount of detail. APPLICATIONS The applications included in this text demonstrate the utility of discrete mathematics in the solution of real-world problems. This text includes applications to a wide variety of areas, including computer science, data networking, psychology, chemistry, engineering, linguistics, biology, business, and the Internet. ALGORITHMS Results in discrete mathematics are often expressed in terms of algorithms; hence, key algorithms are introduced in each chapter of the book. These algorithms are expressed in words and in an easily understood form of structured pseudocode, which is described and specified in Appendix 3. The computational complexity of the algorithms in the text is also analyzed at an elementary level. HISTORICAL INFORMATION The background of many topics is succinctly described in the text. Brief biographies of 83 mathematicians and computer scientists are included as footnotes. These biographies include information about the lives, careers, and accomplishments of these important contributors to discrete mathematics and images, when available, are displayed. In addition, numerous historical footnotes are included that supplement the historical information in the main body of the text. Efforts have been made to keep the book up-to-date by reflecting the latest discoveries. KEY TERMS AND RESULTS A list of key terms and results follows each chapter. The key terms include only the most important that students should learn, and not every term defined in the chapter. EXERCISES There are over 4000 exercises in the text, with many different types of questions posed. There is an ample supply of straightforward exercises that develop basic skills, a large number of intermediate exercises, and many challenging exercises. Exercises are stated clearly and unambiguously, and all are carefully graded for level of difficulty. Exercise sets contain special discussions that develop new concepts not covered in the text, enabling students to discover new ideas through their own work. Exercises that are somewhat more difficult than average are marked with a single star ∗ ; those that are much more challenging are marked with two stars ∗∗ . Exercises whose solutions require calculus are explicitly noted. Exercises that develop results used in the text are clearly . Answers or outlined solutions to all oddidentified with the right pointing hand symbol P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T xii T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Preface numbered exercises are provided at the back of the text. The solutions include proofs in which most of the steps are clearly spelled out. REVIEW QUESTIONS A set of review questions is provided at the end of each chapter. These questions are designed to help students focus their study on the most important concepts and techniques of that chapter. To answer these questions students need to write long answers, rather than just perform calculations or give short replies. SUPPLEMENTARY EXERCISE SETS Each chapter is followed by a rich and varied set of supplementary exercises. These exercises are generally more difficult than those in the exercise sets following the sections. The supplementary exercises reinforce the concepts of the chapter and integrate different topics more effectively. COMPUTER PROJECTS Each chapter is followed by a set of computer projects. The approximately 150 computer projects tie together what students may have learned in computing and in discrete mathematics. Computer projects that are more difficult than average, from both a mathematical and a programming point of view, are marked with a star, and those that are extremely challenging are marked with two stars. COMPUTATIONS AND EXPLORATIONS A set of computations and explorations is included at the conclusion of each chapter. These exercises (approximately 120 in total) are designed to be completed using existing software tools, such as programs that students or instructors have written or mathematical computation packages such as MapleTM or MathematicaTM . Many of these exercises give students the opportunity to uncover new facts and ideas through computation. (Some of these exercises are discussed in the Exploring Discrete Mathematics companion workbooks available online.) WRITING PROJECTS Each chapter is followed by a set of writing projects. To do these projects students need to consult the mathematical literature. Some of these projects are historical in nature and may involve looking up original sources. Others are designed to serve as gateways to new topics and ideas. All are designed to expose students to ideas not covered in depth in the text. These projects tie mathematical concepts together with the writing process and help expose students to possible areas for future study. (Suggested references for these projects can be found online or in the printed Student’s Solutions Guide.) APPENDIXES There are three appendixes to the text. The first introduces axioms for real numbers and the positive integers, and illustrates how facts are proved directly from these axioms. The second covers exponential and logarithmic functions, reviewing some basic material used heavily in the course. The third specifies the pseudocode used to describe algorithms in this text. SUGGESTED READINGS A list of suggested readings for the overall book and for each chapter is provided after the appendices. These suggested readings include books at or below the level of this text, more difficult books, expository articles, and articles in which discoveries in discrete mathematics were originally published. Some of these publications are classics, published many years ago, while others have been published in the last few years. How to Use This Book This text has been carefully written and constructed to support discrete mathematics courses at several levels and with differing foci. The following table identifies the core and optional sections. An introductory one-term course in discrete mathematics at the sophomore level can be based on the core sections of the text, with other sections covered at the discretion of the P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Preface xiii instructor. A two-term introductory course can include all the optional mathematics sections in addition to the core sections. A course with a strong computer science emphasis can be taught by covering some or all of the optional computer science sections. Instructors can find sample syllabi for a wide range of discrete mathematics courses and teaching suggestions for using each section of the text can be found in the Instructor’s Resource Guide available on the website for this book. Chapter Core 1 2 3 4 5 6 7 8 9 10 11 12 13 1.1–1.8 (as needed) 2.1–2.4, 2.6 (as needed) 4.1–4.4 (as needed) 5.1–5.3 6.1–6.3 7.1 8.1, 8.5 9.1, 9.3, 9.5 10.1–10.5 11.1 Optional CS Optional Math 2.5 3.1–3.3 (as needed) 4.5, 4.6 5.4, 5.5 6.6 7.4 8.3 9.2 11.2, 11.3 12.1–12.4 13.1–13.5 6.4, 6.5 7.2, 7.3 8.2, 8.4, 8.6 9.4, 9.6 10.6–10.8 11.4, 11.5 Instructors using this book can adjust the level of difficulty of their course by choosing either to cover or to omit the more challenging examples at the end of sections, as well as the more challenging exercises. The chapter dependency chart shown here displays the strong dependencies. A star indicates that only relevant sections of the chapter are needed for study of a later chapter. Weak dependencies have been ignored. More details can be found in the Instructor Resource Guide. Chapter 1 Chapter 2* Chapter 12 Chapter 3* Chapter 9* Chapter 4* Chapter 10* Chapter 11 Chapter 13 Chapter 5* Chapter 6* Chapter 7 Chapter 8 Ancillaries STUDENT’S SOLUTIONS GUIDE This student manual, available separately, contains full solutions to all odd-numbered problems in the exercise sets. These solutions explain why a particular method is used and why it works. For some exercises, one or two other possible approaches are described to show that a problem can be solved in several different ways. Suggested references for the writing projects found at the end of each chapter are also included in this volume. Also included are a guide to writing proofs and an extensive description of common P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T xiv T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Preface mistakes students make in discrete mathematics, plus sample tests and a sample crib sheet for each chapter designed to help students prepare for exams. (ISBN-10: 0-07-735350-1) (ISBN-13: 978-0-07-735350-6) INSTRUCTOR’S RESOURCE GUIDE This manual, available on the website and in printed form by request for instructors, contains full solutions to even-numbered exercises in the text. Suggestions on how to teach the material in each chapter of the book are provided, including the points to stress in each section and how to put the material into perspective. It also offers sample tests for each chapter and a test bank containing over 1500 exam questions to choose from. Answers to all sample tests and test bank questions are included. Finally, several sample syllabi are presented for courses with differing emphases and student ability levels. (ISBN-10: 0-07-735349-8) (ISBN-13: 978-0-07-735349-0) Acknowledgments I would like to thank the many instructors and students at a variety of schools who have used this book and provided me with their valuable feedback and helpful suggestions. Their input has made this a much better book than it would have been otherwise. I especially want to thank Jerrold Grossman, Jean-Claude Evard, and Georgia Mederer for their technical reviews of the seventh edition and their “eagle eyes,” which have helped ensure the accuracy of this book. I also appreciate the help provided by all those who have submitted comments via the website. I thank the reviewers of this seventh and the six previous editions. These reviewers have provided much helpful criticism and encouragement to me. I hope this edition lives up to their high expectations. Reviewers for the Seventh Edition Philip Barry University of Minnesota, Minneapolis Miklos Bona University of Florida Kirby Brown Queens College John Carter University of Toronto Narendra Chaudhari Nanyang Technological University Allan Cochran University of Arkansas Daniel Cunningham Buffalo State College George Davis Georgia State University Andrzej Derdzinski The Ohio State University Ronald Dotzel University of Missouri-St. Louis T.J. Duda Columbus State Community College Bruce Elenbogen University of Michigan, Dearborn Norma Elias Purdue University, Calumet-Hammond Herbert Enderton University of California, Los Angeles Anthony Evans Wright State University Kim Factor Marquette University Margaret Fleck University of Illinois, Champaign Peter Gillespie Fayetteville State University Johannes Hattingh Georgia State University Ken Holladay University of New Orleans Jerry Ianni LaGuardia Community College Ravi Janardan University of Minnesota, Minneapolis Norliza Katuk University of Utara Malaysia William Klostermeyer University of North Florida Przemo Kranz University of Mississippi Jaromy Kuhl University of West Florida Loredana Lanzani University of Arkansas, Fayetteville Steven Leonhardi Winona State University Xu Liutong Beijing University of Posts and Telecommunications Vladimir Logvinenko De Anza Community College P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 Preface Darrell Minor Chris Rodger Columbus State Community College Keith Olson Auburn University Sukhit Singh Utah Valley University Texas State University, San Marcos Yongyuth Permpoontanalarp King Mongkut’s University of Technology, Thonburi Galin Piatniskaia David Snyder Texas State University, San Marcos Wasin So University of Missouri, St. Louis Stefan Robila San Jose State University Bogdan Suceava Montclair State University California State University, Fullerton xv Christopher Swanson Ashland University Bon Sy Queens College Matthew Walsh Indiana-Purdue University, Fort Wayne Gideon Weinstein Western Governors University David Wilczynski University of Southern California I would like to thank Bill Stenquist, Executive Editor, for his advocacy, enthusiasm, and support. His assistance with this edition has been essential. I would also like to thank the original editor, Wayne Yuhasz, whose insights and skills helped ensure the book’s success, as well as all the many other previous editors of this book. I want to express my appreciation to the staff of RPK Editorial Services for their valuable work on this edition, including Rose Kernan, who served as both the developmental editor and the production editor, and the other members of the RPK team, Fred Dahl, Martha McMaster, Erin Wagner, Harlan James, and Shelly Gerger-Knecthl. I thank Paul Mailhot of PreTeX, Inc., the compositor, for the tremendous amount to work he devoted to producing this edition, and for his intimate knowledge of LaTeX. Thanks also to Danny Meldung of Photo Affairs, Inc., who was resourceful obtaining images for the new biographical footnotes. The accuracy and quality of this new edition owe much to Jerry Grossman and Jean-Claude Evard, who checked the entire manuscript for technical accuracy and Georgia Mederer, who checked the accuracy of the answers at the end of the book and the solutions in the Student’s Solutions Guide and Instructor’s Resource Guide. As usual, I cannot thank Jerry Grossman enough for all his work authoring these two essential ancillaries. I would also express my appreciation the Science, Engineering, and Mathematics (SEM) Division of McGraw-Hill Higher Education for their valuable support for this new edition and the associated media content. In particular, thanks go to Kurt Strand: President, SEM, McGrawHill Higher Education, Marty Lange: Editor-in-Chief, SEM, Michael Lange: Editorial Director, Raghothaman Srinivasan: Global Publisher, Bill Stenquist: Executive Editor, Curt Reynolds: Executive Marketing Manager, Robin A. Reed: Project Manager, Sandy Ludovissey: Buyer, Lorraine Buczek: In-house Developmental Editor, Brenda Rowles: Design Coordinator, Carrie K. Burger: Lead Photo Research Coordinator, and Tammy Juran: Media Project Manager. Kenneth H. Rosen P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 The Companion Website T he extensive companion website accompanying this text has been substantially enhanced for the seventh edition This website is accessible at www.mhhe.com/rosen. The homepage shows the Information Center, and contains login links for the site’s Student Site and Instructor Site. Key features of each area are described below: THE INFORMATION CENTER The Information Center contains basic information about the book including the expanded table of contents (including subsection heads), the preface, descriptions of the ancillaries, and a sample chapter. It also provides a link that can be used to submit errata reports and other feedback about the book. STUDENT SITE The Student site contains a wealth of resources available for student use, including the following, tied into the text wherever the special icons displayed below are found in the text:     Extra Examples You can find a large number of additional examples on the site, covering all chapters of the book. These examples are concentrated in areas where students often ask for additional material. Although most of these examples amplify the basic concepts, more-challenging examples can also be found here. Interactive Demonstration Applets These applets enable you to interactively explore how important algorithms work, and are tied directly to material in the text with linkages to examples and exercises. Additional resources are provided on how to use and apply these applets. Self Assessments These interactive guides help you assess your understanding of 14 key concepts, providing a question bank where each question includes a brief tutorial followed by a multiple-choice question. If you select an incorrect answer, advice is provided to help you understand your error. Using these Self Assessments, you should be able to diagnose your problems and find appropriate help. Web Resources Guide This guide provides annotated links to hundreds of external websites containing relevant material such as historical and biographical information, puzzles and problems, discussions, applets, programs, and more. These links are keyed to the text by page number. Additional resources in the Student site include: xvi  Exploring Discrete Mathematics This ancillary provides help for using a computer algebra system to do a wide range of computations in discrete mathematics. Each chapter provides a description of relevant functions in the computer algebra system and how they are used, programs to carry out computations in discrete mathematics, examples, and exercises that can be worked using this computer algebra system. Two versions, Exploring Discrete Mathematics with MapleTM and Exploring Discrete Mathematics with MathematicaTM will be available.  Applications of Discrete Mathematics This ancillary contains 24 chapters—each with its own set of exercises—presenting a wide variety of interesting and important applications P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 The Companion Website xvii covering three general areas in discrete mathematics: discrete structures, combinatorics, and graph theory. These applications are ideal for supplementing the text or for independent study.     A Guide to Proof-Writing This guide provides additional help for writing proofs, a skill that many students find difficult to master. By reading this guide at the beginning of the course and periodically thereafter when proof writing is required, you will be rewarded as your proof-writing ability grows. (Also available in the Student’s Solutions Guide.) Common Mistakes in Discrete Mathematics This guide includes a detailed list of common misconceptions that students of discrete mathematics often have and the kinds of errors they tend to make. You are encouraged to review this list from time to time to help avoid these common traps. (Also available in the Student’s Solutions Guide.) Advice on Writing Projects This guide offers helpful hints and suggestions for the Writing Projects in the text, including an extensive bibliography of helpful books and articles for research; discussion of various resources available in print and online; tips on doing library research; and suggestions on how to write well. (Also available in the Student’s Solutions Guide.) The Virtual Discrete Mathematics Tutor This extensive ancillary provides students with valuable assistance as they make the transition from lower-level courses to discrete mathematics. The errors students have made when studying discrete mathematics using this text has been analyzed to design this resource. Students will be able to get many of their questions answered and can overcome many obstacles via this ancillaries. The Virtual Discrete Mathematics Tutor is expected to be available in the fall of 2012. INSTRUCTOR SITE This part of the website provides access to all of the resources on the Student Site, as well as these resources for instructors:  Suggested Syllabi Detailed course outlines are shown, offering suggestions for courses with different emphases and different student backgrounds and ability levels.  Teaching Suggestions This guide contains detailed teaching suggestions for instructors, including chapter overviews for the entire text, detailed remarks on each section, and comments on the exercise sets.  Printable Tests Printable tests are offered in TeX and Word format for every chapter, and can be customized by instructors.  PowerPoints Lecture Slides and PowerPoint Figures and Tables An extensive collection of PowerPoint slides for all chapters of the text are provided for instructor use. In addition, images of all figures and tables from the text are provided as PowerPoint slides.  Homework Delivery System An extensive homework delivery system, under development for availability in fall 2012, will provide questions tied directly to the text, so that students will be able to do assignments on-line. Moreover, they will be able to use this system in a tutorial mode. This system will be able to automatically grade assignments, and deliver freeform student input to instructors for their own analysis. Course management capabilities will be provided that will allow instructors to create assignments, automatically assign and grade homework, quiz, and test questions from a bank of questions tied directly to the text, create and edit their own questions, manage course announcements and due dates, and track student progress. P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 To the Student W hat is discrete mathematics? Discrete mathematics is the part of mathematics devoted to the study of discrete objects. (Here discrete means consisting of distinct or unconnected elements.) The kinds of problems solved using discrete mathematics include:  How many ways are there to choose a valid password on a computer system?  What is the probability of winning a lottery?  Is there a link between two computers in a network?  How can I identify spam e-mail messages?  How can I encrypt a message so that no unintended recipient can read it?  What is the shortest path between two cities using a transportation system?  How can a list of integers be sorted so that the integers are in increasing order?  How many steps are required to do such a sorting?  How can it be proved that a sorting algorithm correctly sorts a list?  How can a circuit that adds two integers be designed?  How many valid Internet addresses are there? You will learn the discrete structures and techniques needed to solve problems such as these. More generally, discrete mathematics is used whenever objects are counted, when relationships between finite (or countable) sets are studied, and when processes involving a finite number of steps are analyzed. A key reason for the growth in the importance of discrete mathematics is that information is stored and manipulated by computing machines in a discrete fashion. WHY STUDY DISCRETE MATHEMATICS? There are several important reasons for studying discrete mathematics. First, through this course you can develop your mathematical maturity: that is, your ability to understand and create mathematical arguments. You will not get very far in your studies in the mathematical sciences without these skills. Second, discrete mathematics is the gateway to more advanced courses in all parts of the mathematical sciences. Discrete mathematics provides the mathematical foundations for many computer science courses including data structures, algorithms, database theory, automata theory, formal languages, compiler theory, computer security, and operating systems. Students find these courses much more difficult when they have not had the appropriate mathematical foundations from discrete math. One student has sent me an e-mail message saying that she used the contents of this book in every computer science course she took! Math courses based on the material studied in discrete mathematics include logic, set theory, number theory, linear algebra, abstract algebra, combinatorics, graph theory, and probability theory (the discrete part of the subject). Also, discrete mathematics contains the necessary mathematical background for solving problems in operations research (including many discrete optimization techniques), chemistry, engineering, biology, and so on. In the text, we will study applications to some of these areas. Many students find their introductory discrete mathematics course to be significantly more challenging than courses they have previously taken. One reason for this is that one of the primary goals of this course is to teach mathematical reasoning and problem solving, rather than a discrete set of skills. The exercises in this book are designed to reflect this goal. Although there are plenty of exercises in this text similar to those addressed in the examples, a large xviii P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 To the Student xix percentage of the exercises require original thought. This is intentional. The material discussed in the text provides the tools needed to solve these exercises, but your job is to successfully apply these tools using your own creativity. One of the primary goals of this course is to learn how to attack problems that may be somewhat different from any you may have previously seen. Unfortunately, learning how to solve only particular types of exercises is not sufficient for success in developing the problem-solving skills needed in subsequent courses and professional work. This text addresses many different topics, but discrete mathematics is an extremely diverse and large area of study. One of my goals as an author is to help you develop the skills needed to master the additional material you will need in your own future pursuits. THE EXERCISES I would like to offer some advice about how you can best learn discrete mathematics (and other subjects in the mathematical and computing sciences).You will learn the most by actively working exercises. I suggest that you solve as many as you possibly can. After working the exercises your instructor has assigned, I encourage you to solve additional exercises such as those in the exercise sets following each section of the text and in the supplementary exercises at the end of each chapter. (Note the key explaining the markings preceding exercises.) Key to the Exercises no marking ∗ ∗∗ (Requires calculus ) A routine exercise A difficult exercise An extremely challenging exercise An exercise containing a result used in the book (Table 1 on the following page shows where these exercises are used.) An exercise whose solution requires the use of limits or concepts from differential or integral calculus The best approach is to try exercises yourself before you consult the answer section at the end of this book. Note that the odd-numbered exercise answers provided in the text are answers only and not full solutions; in particular, the reasoning required to obtain answers is omitted in these answers. The Student’s Solutions Guide, available separately, provides complete, worked solutions to all odd-numbered exercises in this text. When you hit an impasse trying to solve an odd-numbered exercise, I suggest you consult the Student’s Solutions Guide and look for some guidance as to how to solve the problem. The more work you do yourself rather than passively reading or copying solutions, the more you will learn. The answers and solutions to the evennumbered exercises are intentionally not available from the publisher; ask your instructor if you have trouble with these. WEB RESOURCES You are strongly encouraged to take advantage of additional resources available on the Web, especially those on the companion website for this book found at www.mhhe.com/rosen. You will find many Extra Examples designed to clarify key concepts; Self Assessments for gauging how well you understand core topics; Interactive Demonstration Applets exploring key algorithms and other concepts; a Web Resources Guide containing an extensive selection of links to external sites relevant to the world of discrete mathematics; extra explanations and practice to help you master core concepts; added instruction on writing proofs and on avoiding common mistakes in discrete mathematics; in-depth discussions of important applications; and guidance on utilizing MapleTM software to explore the computational aspects of discrete mathematics. Places in the text where these additional online resources are available are identified in the margins by special icons. You will also find (after fall 2012) the Virtual Discrete Mathematics Tutor, an on-line resource that provides extra support to help you make the transition from lower level courses to discrete mathematics. This tutorial should help answer many of your questions and correct errors that you may make, based on errors other students using this book, have made. For more details on these and other online resources, see the description of the companion website immediately preceding this “To the Student” message. P1: 1/1 FRONT-7T P2: 1/2 QC: 1/1 Rosen-2311T xx T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 10:21 To the Student TABLE 1 Hand-Icon Exercises and Where They Are Used Section Exercise Section Where Used Pages Where Used 1.1 40 1.3 31 1.1 41 1.3 31 1.3 9 1.6 71 1.3 10 1.6 70, 71 1.3 15 1.6 71 1.3 30 1.6 71, 74 1.3 42 12.2 820 1.7 16 1.7 86 2.3 72 2.3 144 2.3 79 2.5 170 2.5 15 2.5 174 2.5 16 2.5 173 3.1 43 3.1 197 3.2 72 11.2 761 4.2 36 4.2 270 4.3 37 4.1 239 4.4 2 4.6 301 4.4 44 7.2 464 6.4 17 7.2 466 6.4 21 7.4 480 7.2 15 7.2 466 9.1 26 9.4 598 10.4 59 11.1 747 11.1 15 11.1 750 11.1 30 11.1 755 11.1 48 11.2 762 12.1 12 12.3 825 A.2 4 8.3 531 THE VALUE OF THIS BOOK My intention is to make your substantial investment in this text an excellent value. The book, the associated ancillaries, and companion website have taken many years of effort to develop and refine. I am confident that most of you will find that the text and associated materials will help you master discrete mathematics, just as so many previous students have. Even though it is likely that you will not cover some chapters in your current course, you should find it helpful—as many other students have—to read the relevant sections of the book as you take additional courses. Most of you will return to this book as a useful tool throughout your future studies, especially for those of you who continue in computer science, mathematics, and engineering. I have designed this book to be a gateway for future studies and explorations, and to be comprehensive reference, and I wish you luck as you begin your journey. Kenneth H. Rosen P1: 1/1 CH01-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 15:27 C H A P T E R 1 1.1 Propositional Logic 1.2 Applications of Propositional Logic 1.3 Propositional Equivalences 1.4 Predicates and Quantifiers 1.5 Nested Quantifiers 1.6 Rules of Inference 1.7 Introduction to Proofs 1.8 Proof Methods and Strategy 1.1 The Foundations: Logic and Proofs T he rules of logic specify the meaning of mathematical statements. For instance, these rules help us understand and reason with statements such as “There exists an integer that is not the sum of two squares” and “For every positive integer n, the sum of the positive integers not exceeding n is n(n + 1)/2.” Logic is the basis of all mathematical reasoning, and of all automated reasoning. It has practical applications to the design of computing machines, to the specification of systems, to artificial intelligence, to computer programming, to programming languages, and to other areas of computer science, as well as to many other fields of study. To understand mathematics, we must understand what makes up a correct mathematical argument, that is, a proof. Once we prove a mathematical statement is true, we call it a theorem. A collection of theorems on a topic organize what we know about this topic. To learn a mathematical topic, a person needs to actively construct mathematical arguments on this topic, and not just read exposition. Moreover, knowing the proof of a theorem often makes it possible to modify the result to fit new situations. Everyone knows that proofs are important throughout mathematics, but many people find it surprising how important proofs are in computer science. In fact, proofs are used to verify that computer programs produce the correct output for all possible input values, to show that algorithms always produce the correct result, to establish the security of a system, and to create artificial intelligence. Furthermore, automated reasoning systems have been created to allow computers to construct their own proofs. In this chapter, we will explain what makes up a correct mathematical argument and introduce tools to construct these arguments. We will develop an arsenal of different proof methods that will enable us to prove many different types of results. After introducing many different methods of proof, we will introduce several strategies for constructing proofs. We will introduce the notion of a conjecture and explain the process of developing mathematics by studying conjectures. Propositional Logic Introduction The rules of logic give precise meaning to mathematical statements. These rules are used to distinguish between valid and invalid mathematical arguments. Because a major goal of this book is to teach the reader how to understand and how to construct correct mathematical arguments, we begin our study of discrete mathematics with an introduction to logic. Besides the importance of logic in understanding mathematical reasoning, logic has numerous applications to computer science. These rules are used in the design of computer circuits, the construction of computer programs, the verification of the correctness of programs, and in many other ways. Furthermore, software systems have been developed for constructing some, but not all, types of proofs automatically. We will discuss these applications of logic in this and later chapters. 1 P2: 1/2 QC: 1/1 Rosen-2311T 2 T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 15:27 1 / The Foundations: Logic and Proofs Propositions Our discussion begins with an introduction to the basic building blocks of logic—propositions. A proposition is a declarative sentence (that is, a sentence that declares a fact) that is either true or false, but not both. EXAMPLE 1 All the following declarative sentences are propositions. 1. 2. 3. 4. Washington, D.C., is the capital of the United States of America. Toronto is the capital of Canada. 1 + 1 = 2. 2 + 2 = 3. Propositions 1 and 3 are true, whereas 2 and 4 are false. ▲ CH01-7T Some sentences that are not propositions are given in Example 2. EXAMPLE 2 Consider the following sentences. 1. 2. 3. 4. What time is it? Read this carefully. x + 1 = 2. x + y = z. Sentences 1 and 2 are not propositions because they are not declarative sentences. Sentences 3 and 4 are not propositions because they are neither true nor false. Note that each of sentences 3 and 4 can be turned into a proposition if we assign values to the variables. We will also discuss other ways to turn sentences such as these into propositions in Section 1.4. ▲ P1: 1/1 We use letters to denote propositional variables (or statement variables), that is, variables that represent propositions, just as letters are used to denote numerical variables. The ARISTOTLE (384 b.c.e.–322 b.c.e.) Aristotle was born in Stagirus (Stagira) in northern Greece. His father was the personal physician of the King of Macedonia. Because his father died when Aristotle was young, Aristotle could not follow the custom of following his father’s profession. Aristotle became an orphan at a young age when his mother also died. His guardian who raised him taught him poetry, rhetoric, and Greek. At the age of 17, his guardian sent him to Athens to further his education. Aristotle joined Plato’s Academy, where for 20 years he attended Plato’s lectures, later presenting his own lectures on rhetoric. When Plato died in 347 B.C.E., Aristotle was not chosen to succeed him because his views differed too much from those of Plato. Instead, Aristotle joined the court of King Hermeas where he remained for three years, and married the niece of the King. When the Persians defeated Hermeas, Aristotle moved to Mytilene and, at the invitation of King Philip of Macedonia, he tutored Alexander, Philip’s son, who later became Alexander the Great. Aristotle tutored Alexander for five years and after the death of King Philip, he returned to Athens and set up his own school, called the Lyceum. Aristotle’s followers were called the peripatetics, which means “to walk about,” because Aristotle often walked around as he discussed philosophical questions. Aristotle taught at the Lyceum for 13 years where he lectured to his advanced students in the morning and gave popular lectures to a broad audience in the evening. When Alexander the Great died in 323 B.C.E., a backlash against anything related to Alexander led to trumped-up charges of impiety against Aristotle. Aristotle fled to Chalcis to avoid prosecution. He only lived one year in Chalcis, dying of a stomach ailment in 322 B.C.E. Aristotle wrote three types of works: those written for a popular audience, compilations of scientific facts, and systematic treatises. The systematic treatises included works on logic, philosophy, psychology, physics, and natural history. Aristotle’s writings were preserved by a student and were hidden in a vault where a wealthy book collector discovered them about 200 years later. They were taken to Rome, where they were studied by scholars and issued in new editions, preserving them for posterity. P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 15:27 1.1 Propositional Logic 3 conventional letters used for propositional variables are p, q, r, s, . . . . The truth value of a proposition is true, denoted by T, if it is a true proposition, and the truth value of a proposition is false, denoted by F, if it is a false proposition. The area of logic that deals with propositions is called the propositional calculus or propositional logic. It was first developed systematically by the Greek philosopher Aristotle more than 2300 years ago. We now turn our attention to methods for producing new propositions from those that we already have. These methods were discussed by the English mathematician George Boole in 1854 in his book The Laws of Thought. Many mathematical statements are constructed by combining one or more propositions. New propositions, called compound propositions, are formed from existing propositions using logical operators. DEFINITION 1 Let p be a proposition. The negation of p, denoted by ¬p (also denoted by p), is the statement “It is not the case that p.” The proposition ¬p is read “not p.” The truth value of the negation of p, ¬p, is the opposite of the truth value of p. EXAMPLE 3 Find the negation of the proposition “Michael’s PC runs Linux” and express this in simple English. Solution: The negation is “It is not the case that Michael’s PC runs Linux.” This negation can be more simply expressed as “Michael’s PC does not run Linux.” EXAMPLE 4 ▲ CH01-7T Find the negation of the proposition “Vandana’s smartphone has at least 32GB of memory” and express this in simple English. Solution: The negation is “It is not the case that Vandana’s smartphone has at least 32GB of memory.” This negation can also be expressed as “Vandana’s smartphone does not have at least 32GB of memory” or even more simply as “Vandana’s smartphone has less than 32GB of memory.” ▲ P1: 1/1 CH01-7T P2: 1/2 QC: 1/1 Rosen-2311T 4 T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 15:27 1 / The Foundations: Logic and Proofs TABLE 1 The Truth Table for the Negation of a Proposition. p ¬p T F F T DEFINITION 2 Table 1 displays the truth table for the negation of a proposition p. This table has a row for each of the two possible truth values of a proposition p. Each row shows the truth value of ¬p corresponding to the truth value of p for this row. The negation of a proposition can also be considered the result of the operation of the negation operator on a proposition. The negation operator constructs a new proposition from a single existing proposition. We will now introduce the logical operators that are used to form new propositions from two or more existing propositions. These logical operators are also called connectives. Let p and q be propositions. The conjunction of p and q, denoted by p ∧ q, is the proposition “p and q.” The conjunction p ∧ q is true when both p and q are true and is false otherwise. Table 2 displays the truth table of p ∧ q. This table has a row for each of the four possible combinations of truth values of p and q. The four rows correspond to the pairs of truth values TT, TF, FT, and FF, where the first truth value in the pair is the truth value of p and the second truth value is the truth value of q. Note that in logic the word “but” sometimes is used instead of “and” in a conjunction. For example, the statement “The sun is shining, but it is raining” is another way of saying “The sun is shining and it is raining.” (In natural language, there is a subtle difference in meaning between “and” and “but”; we will not be concerned with this nuance here.) EXAMPLE 5 Find the conjunction of the propositions p and q where p is the proposition “Rebecca’s PC has more than 16 GB free hard disk space” and q is the proposition “The processor in Rebecca’s PC runs faster than 1 GHz.” Solution: The conjunction of these propositions, p ∧ q, is the proposition “Rebecca’s PC has more than 16 GB free hard disk space, and the processor in Rebecca’s PC runs faster than 1 GHz.” This conjunction can be expressed more simply as “Rebecca’s PC has more than 16 GB free hard disk space, and its processor runs faster than 1 GHz.” For this conjunction to be true, both conditions given must be true. It is false, when one or both of these conditions are false. ▲ P1: 1/1 DEFINITION 3 Let p and q be propositions. The disjunction of p and q, denoted by p ∨ q, is the proposition “p or q.” The disjunction p ∨ q is false when both p and q are false and is true otherwise. Table 3 displays the truth table for p ∨ q. TABLE 2 The Truth Table for TABLE 3 The Truth Table for the Conjunction of Two Propositions. the Disjunction of Two Propositions. p q p∧q p q p∨q T T F F T F T F T F F F T T F F T F T F T T T F CH01-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 15:27 1.1 Propositional Logic 5 The use of the connective or in a disjunction corresponds to one of the two ways the word or is used in English, namely, as an inclusive or. A disjunction is true when at least one of the two propositions is true. For instance, the inclusive or is being used in the statement “Students who have taken calculus or computer science can take this class.” Here, we mean that students who have taken both calculus and computer science can take the class, as well as the students who have taken only one of the two subjects. On the other hand, we are using the exclusive or when we say “Students who have taken calculus or computer science, but not both, can enroll in this class.” Here, we mean that students who have taken both calculus and a computer science course cannot take the class. Only those who have taken exactly one of the two courses can take the class. Similarly, when a menu at a restaurant states, “Soup or salad comes with an entrée,” the restaurant almost always means that customers can have either soup or salad, but not both. Hence, this is an exclusive, rather than an inclusive, or. EXAMPLE 6 What is the disjunction of the propositions p and q where p and q are the same propositions as in Example 5? Solution: The disjunction of p and q, p ∨ q, is the proposition “Rebecca’s PC has at least 16 GB free hard disk space, or the processor in Rebecca’s PC runs faster than 1 GHz.” This proposition is true when Rebecca’s PC has at least 16 GB free hard disk space, when the PC’s processor runs faster than 1 GHz, and when both conditions are true. It is false when both of these conditions are false, that is, when Rebecca’s PC has less than 16 GB free hard disk space and the processor in her PC runs at 1 GHz or slower. ▲ P1: 1/1 As was previously remarked, the use of the connective or in a disjunction corresponds to one of the two ways the word or is used in English, namely, in an inclusive way. Thus, a disjunction is true when at least one of the two propositions in it is true. Sometimes, we use or in an exclusive sense. When the exclusive or is used to connect the propositions p and q, the proposition “p or q (but not both)” is obtained. This proposition is true when p is true and q is false, and when p is false and q is true. It is false when both p and q are false and when both are true. GEORGE BOOLE (1815–1864) George Boole, the son of a cobbler, was born in Lincoln, England, in November 1815. Because of his family’s difficult financial situation, Boole struggled to educate himself while supporting his family. Nevertheless, he became one of the most important mathematicians of the 1800s. Although he considered a career as a clergyman, he decided instead to go into teaching, and soon afterward opened a school of his own. In his preparation for teaching mathematics, Boole—unsatisfied with textbooks of his day— decided to read the works of the great mathematicians. While reading papers of the great French mathematician Lagrange, Boole made discoveries in the calculus of variations, the branch of analysis dealing with finding curves and surfaces by optimizing certain parameters. In 1848 Boole published The Mathematical Analysis of Logic, the first of his contributions to symbolic logic. In 1849 he was appointed professor of mathematics at Queen’s College in Cork, Ireland. In 1854 he published The Laws of Thought, his most famous work. In this book, Boole introduced what is now called Boolean algebra in his honor. Boole wrote textbooks on differential equations and on difference equations that were used in Great Britain until the end of the nineteenth century. Boole married in 1855; his wife was the niece of the professor of Greek at Queen’s College. In 1864 Boole died from pneumonia, which he contracted as a result of keeping a lecture engagement even though he was soaking wet from a rainstorm. P1: 1/1 CH01-7T P2: 1/2 QC: 1/1 Rosen-2311T 6 T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 15:27 1 / The Foundations: Logic and Proofs DEFINITION 4 TABLE 4 The Truth Table for TABLE 5 The Truth Table for the Exclusive Or of Two Propositions. the Conditional Statement p → q. p q p⊕q p q p→q T T F F T F T F F T T F T T F F T F T F T F T T Let p and q be propositions. The exclusive or of p and q, denoted by p ⊕ q, is the proposition that is true when exactly one of p and q is true and is false otherwise. The truth table for the exclusive or of two propositions is displayed in Table 4. Conditional Statements We will discuss several other important ways in which propositions can be combined. DEFINITION 5 Let p and q be propositions. The conditional statement p → q is the proposition “if p, then q.” The conditional statement p → q is false when p is true and q is false, and true otherwise. In the conditional statement p → q, p is called the hypothesis (or antecedent or premise) and q is called the conclusion (or consequence). The statement p → q is called a conditional statement because p → q asserts that q is true on the condition that p holds. A conditional statement is also called an implication. The truth table for the conditional statement p → q is shown in Table 5. Note that the statement p → q is true when both p and q are true and when p is false (no matter what truth value q has). Because conditional statements play such an essential role in mathematical reasoning, a variety of terminology is used to express p → q. You will encounter most if not all of the following ways to express this conditional statement: “if p, then q” “if p, q” “p is sufficient for q” “q if p” “q when p” “a necessary condition for p is q” “q unless ¬p” “p implies q” “p only if q” “a sufficient condition for q is p” “q whenever p” “q is necessary for p” “q follows from p” A useful way to understand the truth value of a conditional statement is to think of an obligation or a contract. For example, the pledge many politicians make when running for office is “If I am elected, then I will lower taxes.” CH01-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 15:27 1.1 Propositional Logic 7 If the politician is elected, voters would expect this politician to lower taxes. Furthermore, if the politician is not elected, then voters will not have any expectation that this person will lower taxes, although the person may have sufficient influence to cause those in power to lower taxes. It is only when the politician is elected but does not lower taxes that voters can say that the politician has broken the campaign pledge. This last scenario corresponds to the case when p is true but q is false in p → q. Similarly, consider a statement that a professor might make: “If you get 100% on the final, then you will get an A.” You might have trouble understanding how “unless” is used in conditional statements unless you read this paragraph carefully. EXAMPLE 7 If you manage to get a 100% on the final, then you would expect to receive an A. If you do not get 100% you may or may not receive an A depending on other factors. However, if you do get 100%, but the professor does not give you an A, you will feel cheated. Of the various ways to express the conditional statement p → q, the two that seem to cause the most confusion are “p only if q” and “q unless ¬p.” Consequently, we will provide some guidance for clearing up this confusion. To remember that “p only if q” expresses the same thing as “if p, then q,” note that “p only if q” says that p cannot be true when q is not true. That is, the statement is false if p is true, but q is false. When p is false, q may be either true or false, because the statement says nothing about the truth value of q. Be careful not to use “q only if p” to express p → q because this is incorrect. To see this, note that the true values of “q only if p” and p → q are different when p and q have different truth values. To remember that “q unless ¬p” expresses the same conditional statement as “if p, then q,” note that “q unless ¬p” means that if ¬p is false, then q must be true. That is, the statement “q unless ¬p” is false when p is true but q is false, but it is true otherwise. Consequently, “q unless ¬p” and p → q always have the same truth value. We illustrate the translation between conditional statements and English statements in Example 7. Let p be the statement “Maria learns discrete mathematics” and q the statement “Maria will find a good job.” Express the statement p → q as a statement in English. Solution: From the definition of conditional statements, we see that when p is the statement “Maria learns discrete mathematics” and q is the statement “Maria will find a good job,” p → q represents the statement “If Maria learns discrete mathematics, then she will find a good job.” There are many other ways to express this conditional statement in English. Among the most natural of these are: “Maria will find a good job when she learns discrete mathematics.” “For Maria to get a good job, it is sufficient for her to learn discrete mathematics.” and “Maria will find a good job unless she does not learn discrete mathematics.” ▲ P1: 1/1 Note that the way we have defined conditional statements is more general than the meaning attached to such statements in the English language. For instance, the conditional statement in Example 7 and the statement “If it is sunny, then we will go to the beach.” are statements used in normal language where there is a relationship between the hypothesis and the conclusion. Further, the first of these statements is true unless Maria learns discrete mathematics, but she does not get a good job, and the second is true unless it is indeed sunny, but we do not go to the beach. On the other hand, the statement CH01-7T P2: 1/2 QC: 1/1 Rosen-2311T 8 T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 15:27 1 / The Foundations: Logic and Proofs “If Juan has a smartphone, then 2 + 3 = 5” is true from the definition of a conditional statement, because its conclusion is true. (The truth value of the hypothesis does not matter then.) The conditional statement “If Juan has a smartphone, then 2 + 3 = 6” is true if Juan does not have a smartphone, even though 2 + 3 = 6 is false. We would not use these last two conditional statements in natural language (except perhaps in sarcasm), because there is no relationship between the hypothesis and the conclusion in either statement. In mathematical reasoning, we consider conditional statements of a more general sort than we use in English. The mathematical concept of a conditional statement is independent of a cause-andeffect relationship between hypothesis and conclusion. Our definition of a conditional statement specifies its truth values; it is not based on English usage. Propositional language is an artificial language; we only parallel English usage to make it easy to use and remember. The if-then construction used in many programming languages is different from that used in logic. Most programming languages contain statements such as if p then S, where p is a proposition and S is a program segment (one or more statements to be executed). When execution of a program encounters such a statement, S is executed if p is true, but S is not executed if p is false, as illustrated in Example 8. EXAMPLE 8 What is the value of the variable x after the statement if 2 + 2 = 4 then x := x + 1 if x = 0 before this statement is encountered? (The symbol := stands for assignment. The statement x := x + 1 means the assignment of the value of x + 1 to x.) Solution: Because 2 + 2 = 4 is true, the assignment statement x := x + 1 is executed. Hence, x has the value 0 + 1 = 1 after this statement is encountered. ▲ P1: 1/1 Remember that the contrapositive, but neither the converse or inverse, of a conditional statement is equivalent to it. CONVERSE, CONTRAPOSITIVE, AND INVERSE We can form some new conditional statements starting with a conditional statement p → q. In particular, there are three related conditional statements that occur so often that they have special names. The proposition q → p is called the converse of p → q. The contrapositive of p → q is the proposition ¬q → ¬p. The proposition ¬p → ¬q is called the inverse of p → q. We will see that of these three conditional statements formed from p → q, only the contrapositive always has the same truth value as p → q. We first show that the contrapositive, ¬q → ¬p, of a conditional statement p → q always has the same truth value as p → q. To see this, note that the contrapositive is false only when ¬p is false and ¬q is true, that is, only when p is true and q is false. We now show that neither the converse, q → p, nor the inverse, ¬p → ¬q, has the same truth value as p → q for all possible truth values of p and q. Note that when p is true and q is false, the original conditional statement is false, but the converse and the inverse are both true. When two compound propositions always have the same truth value we call them equivalent, so that a conditional statement and its contrapositive are equivalent. The converse and the inverse of a conditional statement are also equivalent, as the reader can verify, but neither is equivalent to the original conditional statement. (We will study equivalent propositions in Section 1.3.) Take note that one of the most common logical errors is to assume that the converse or the inverse of a conditional statement is equivalent to this conditional statement. We illustrate the use of conditional statements in Example 9. CH01-7T P2: 1/2 QC: 1/1 Rosen-2311T T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 15:27 1.1 Propositional Logic EXAMPLE 9 9 What are the contrapositive, the converse, and the inverse of the conditional statement “The home team wins whenever it is raining?” Solution: Because “q whenever p” is one of the ways to express the conditional statement p → q, the original statement can be rewritten as “If it is raining, then the home team wins.” Consequently, the contrapositive of this conditional statement is “If the home team does not win, then it is not raining.” The converse is “If the home team wins, then it is raining.” The inverse is “If it is not raining, then the home team does not win.” Only the contrapositive is equivalent to the original statement. ▲ P1: 1/1 BICONDITIONALS We now introduce another way to combine propositions that expresses that two propositions have the same truth value. DEFINITION 6 Let p and q be propositions. The biconditional statement p ↔ q is the proposition “p if and only if q.” The biconditional statement p ↔ q is true when p and q have the same truth values, and is false otherwise. Biconditional statements are also called bi-implications. The truth table for p ↔ q is shown in Table 6. Note that the statement p ↔ q is true when both the conditional statements p → q and q → p are true and is false otherwise. That is why we use the words “if and only if” to express this logical connective and why it is symbolically written by combining the symbols → and ←. There are some other common ways to express p ↔ q: “p is necessary and sufficient for q” “if p then q, and conversely” “p iff q.” The last way of expressing the biconditional statement p ↔ q uses the abbreviation “iff” for “if and only if.” Note that p ↔ q has exactly the same truth value as (p → q) ∧ (q → p). TABLE 6 The Truth Table for the Biconditional p ↔ q. p q p↔q T T F F T F T F T F F T P2: 1/2 QC: 1/1 Rosen-2311T 10 T1: 2 MHIA017-Rosen-v5.cls May 13, 2011 15:27 1 / The Foundations: Logic and Proofs EXAMPLE 10 Let p be the statement “You can take the flight,” and let q be the statement “You buy a ticket.” Then p ↔ q is the statement “You can take the flight if and only if you buy a ticket.” This statement is true if p and q are either both true or both false, that is, if you buy a ticket and can take the flight or if you do not buy a ticket and you cannot take the flight. It is false when p and q have opposite truth values, that is, when you do not buy a ticket, but you can take...