 Analysis of Algorithms  Flajolet, Prodinger
A research site with papers to download, links to researchers, a newsletter, etc. Analysis of Algorithms (AofA) is a field in computer science whose overall goal is an understanding of the complexity of algorithms. While much research is devoted to worstcase evaluations, the focus in these pages is methods for averagecase and probabilistic analysis. Properties of random strings, permutations, trees, and graphs are thus essential ingredients in the analysis of algorithms.
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 MX4002: Algorithms  Ian Craw and John Pulham; University of Aberdeen
Lecture notes, tutorial sheets, exams, and other material provided for a course on algorithms with the objective of exposing the student to a small number of typical methods from a range of different contexts, so as to reveal the type of thinking that is involved and give students the basic hints as to how to proceed with individual problems. Applications include sorting algorithms, searching algorithms, string processing and language, geometric algorithms, graph algorithms, and mathematical algorithms. Individual topics include hatching convex polygons; recursion; optimal sorting; optimal merging; heapsort; grammars and parsing; abstract data types such as the ADT priority queue, traversals, binary trees, and Huffman codes; random shuffles; the Fast Fourier Transform (FFT) and its applications, such as image processing (Gaussian Blur and the Laplace Operator); and Big O timing formulas. Available online as well as in PDF format.
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 The Stony Brook Algorithm Repository  Steven S. Skiena; Dept. of Computer Science, SUNYStony Brook
A comprehensive collection of algorithm implementations for over seventy of the most fundamental problems in combinatorial algorithms. The problem taxonomy, implementations, and supporting material are drawn from Skiena's book The Algorithm Design Manual. Since the practical person is more often looking for a program than an algorithm, Skiena provides pointers to solid implementations of useful algorithms, when they are available. Problems by Category: Data Structures; Numerical Problems; Combinatorial Problems; Graph Problems (polynomialtime problems, hard problems); Computational Geometry; Set and String Problems. Implementations By Language: C++; C; Pascal; FORTRAN; Mathematica; Lisp.
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