Mathematics for Computer Science

I Proofs 1 Propositions 5 1.1 Compound Propositions 6 1.2 Propositional Logic in Computer Programs 10 1.3 Predicates and Quantifiers 11 1.4 Validity 19 1.5 Satisfiability 21 2 Patterns of Proof 23 2.1 The Axiomatic Method 23 2.2 Proof by Cases 26 2.3 Proving an Implication 27 2.4 Proving an “If and Only If” 30 2.5 Proof by Contradiction 32 2.6 Proofs about Sets 33 2.7 Good Proofs in Practice 40 3 Induction 43 3.1 The Well Ordering Principle 43 3.2 Ordinary Induction 46 3.3 Invariants 56 3.4 Strong Induction 64 3.5 Structural Induction 69 4 Number Theory 81 4.1 Divisibility 81 4.2 The Greatest Common Divisor 87 4.3 The Fundamental Theorem of Arithmetic 94 4.4 Alan Turing 96 4.5 Modular Arithmetic 100 4.6 Arithmetic with a Prime Modulus 103 4.7 Arithmetic with an Arbitrary Modulus 108 4.8 The RSA Algorithm 113 II Structures 5 Graph Theory 121 5.1 Definitions 121 5.2 Matching Problems 128 5.3 Coloring 143 5.4 Getting from A to B in a Graph 147 5.5 Connectivity 151 5.6 Around and Around We Go 156 5.7 Trees 162 5.8 Planar Graphs 170 6 Directed Graphs 189 6.1 Definitions 189 6.2 Tournament Graphs 192 6.3 Communication Networks 196 7 Relations and Partial Orders 213 7.1 Binary Relations 213 7.2 Relations and Cardinality 217 7.3 Relations on One Set 220 7.4 Equivalence Relations 222 7.5 Partial Orders 225 7.6 Posets and DAGs 226 7.7 Topological Sort 229 7.8 Parallel Task Scheduling 232 7.9 Dilworth’s Lemma 235 8 State Machines 237 III Counting 9 Sums and Asymptotics 243 9.1 The Value of an Annuity 244 9.2 Power Sums 250 9.3 Approximating Sums 252 9.4 Hanging Out Over the Edge 257 9.5 Double Trouble 269 9.6 Products 272 9.7 Asymptotic Notation 275 10 Recurrences 283 10.1 The Towers of Hanoi 284 10.2 Merge Sort 291 10.3 Linear Recurrences 294 10.4 Divide-and-Conquer Recurrences 302 10.5 A Feel for Recurrences 309 11 Cardinality Rules 313 11.1 Counting One Thing by Counting Another 313 11.2 Counting Sequences 314 11.3 The Generalized Product Rule 317 11.4 The Division Rule 321 11.5 Counting Subsets 324 11.6 Sequences with Repetitions 326 11.7 Counting Practice: Poker Hands 329 11.8 Inclusion-Exclusion 334 11.9 Combinatorial Proofs 339 11.10 The Pigeonhole Principle 342 11.11 A Magic Trick 346 12 Generating Functions 355 12.1 Definitions and Examples 355 12.2 Operations on Generating Functions 356 12.3 Evaluating Sums 361 12.4 Extracting Coefficients 363 12.5 Solving Linear Recurrences 370 12.6 Counting with Generating Functions 374 13 Infinite Sets 379 13.1 Injections, Surjections, and Bijections 379 13.2 Countable Sets 381 13.3 Power Sets Are Strictly Bigger 384 13.4 Infinities in Computer Science 386 IV Probability 14 Events and Probability Spaces 391 14.1 Let’s Make a Deal 391 14.2 The Four Step Method 392 14.3 Strange Dice 402 14.4 Set Theory and Probability 411 14.5 Infinite Probability Spaces 413 15 Conditional Probability 417 15.1 Definition 417 15.2 Using the Four-Step Method to Determine Conditional Probability 418 15.3 A Posteriori Probabilities 424 15.4 Conditional Identities 427 16 Independence 431 16.1 Definitions 431 16.2 Independence Is an Assumption 432 16.3 Mutual Independence 433 16.4 Pairwise Independence 435 16.5 The Birthday Paradox 438 17 Random Variables and Distributions 445 17.1 Definitions and Examples 445 17.2 Distribution Functions 450 17.3 Bernoulli Distributions 452 17.4 Uniform Distributions 453 17.5 Binomial Distributions 456 18 Expectation 467 18.1 Definitions and Examples 467 18.2 Expected Returns in Gambling Games 477 18.3 Expectations of Sums 483 18.4 Expectations of Products 490 18.5 Expectations of Quotients 492 19 Deviations 497 19.1 Variance 497 19.2 Markov’s Theorem 507 19.3 Chebyshev’s Theorem 513 19.4 Bounds for Sums of Random Variables 516 19.5 Mutually Independent Events 523 20 Random Walks 533 20.1 Unbiased Random Walks 533 20.2 Gambler’s Ruin 542 20.3 Walking in Circles 549

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