The design and analysis of algorithms is one of the two essential cornerstone topics in computer science (the other being automata theory/theory of computation). Every computer scientist has a copy of Knuth's works on algorithms on his or her shelf. Dexter Kozen, a researcher and professor at Cornell University, has written a text for graduate study of algorithms.

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These are my lecture notes from CS681: Design and Analysis of Algo­ rithms, a one-semester graduate course I taught at Cornell for three consec­ utive fall semesters from '88 to '90. The course serves a dual purpose: to cover core material in algorithms for graduate students in computer science preparing for their PhD qualifying exams, and to introduce theory students to some advanced topics in the design and analysis of algorithms. The material is thus a mixture of core and advanced topics. At first I meant these notes to supplement and not supplant a textbook, but over the three years they gradually took on a life of their own. In addition to the notes, I depended heavily on the texts A. V. Aho, J. E. Hopcroft, and J. D. Ullman, The Design and Analysis of Computer Algorithms. Addison-Wesley, 1975. M. R. Garey and D. S. Johnson, Computers and Intractibility: A Guide to the Theory of NP-Completeness. w. H. Freeman, 1979. R. E. Tarjan, Data Structures and Network Algorithms. SIAM Regional Conference Series in Applied Mathematics 44, 1983. and still recommend them as excellent references.

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I Lectures.- 1 Algorithms and Their Complexity.- 2 Topological Sort and MST.- 3 Matroids and Independence.- 4 Depth-First and Breadth-First Search.- 5 Shortest Paths and Transitive Closure.- 6 Kleene Algebra.- 7 More on Kleene Algebra.- 8 Binomial Heaps.- 9 Fibonacci Heaps.- 10 Union-Find.- 11 Analysis of Union-Find.- 12 Splay Trees.- 13 Random Search Trees.- 14 Planar and Plane Graphs.- 15 The Planar Separator Theorem.- 16 Max Flow.- 17 More on Max Flow.- 18 Still More on Max Flow.- 19 Matching.- 20 More on Matching.- 21 Reductions and NP-Completeness.- 22 More on Reductions and NP-Completeness.- 23 More NP-Complete Problems.- 24 Still More NP-Complete Problems.- 25 Cook's Theorem.- 26 Counting Problems and #P.- 27 Counting Bipartite Matchings.- 28 Parallel Algorithms and NC.- 29 Hypercubes and the Gray Representation.- 30 Integer Arithmetic in NC.- 31 Csanky's Algorithm.- 32 Chistov's Algorithm.- 33 Matrix Rank.- 34 Linear Equations and Polynomial GCDs.- 35 The Fast Fourier Transform (FFT).- 36 Luby's Algorithm.- 37 Analysis of Luby's Algorithm.- 38 Miller's Primality Test.- 39 Analysis of Miller's Primality Test.- 40 Probabilistic Tests with Polynomials.- II Homework Exercises.- Homework 1.- Homework 2.- Homework 3.- Homework 4.- Homework 5.- Homework 6.- Homework 7.- Homework 8.- Homework 9.- Homework 10.- Miscellaneous Exercises.- III Homework Solutions.- Homework 1 Solutions.- Homework 2 Solutions.- Homework 3 Solutions.- Homework 4 Solutions.- Homework 5 Solutions.- Homework 6 Solutions.- Homework 7 Solutions.- Homework 8 Solutions.- Homework 9 Solutions.- Homework 10 Solutions.- Solutions to Miscellaneous Exercises.