Analysis of Algorithms aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the scientific analysis of algorithms in computer science and for the study of scientific models in many other disciplines, including probability theory, statistical physics, computational biology and information theory. This course covers recurrence relations, generating functions, asymptotics, and fundamental structures such as trees, permutations, strings, tries, words, and mappings, in the context of applications to the analysis of algorithms.
Robert Sedgewick was the founding chair of the Department of Computer Science. Prof. Sedgewick also served on the faculty at Brown University and has held various visiting research positions. Prof. Sedgewick's interests are in analytic combinatorics, algorithm design, the scientific analysis of algorithms, curriculum development, and innovations in the dissemination of knowledge. He has published widely in these areas and is the author of several books.