Data Structures and Algorithms: Annotated Reference with Examples
by Granville Barnett, Luca Del Tongo
Publisher: DotNetSlackers 2008
Number of pages: 112
This book provides implementations of common and uncommon algorithms in pseudocode which is language independent and provides for easy porting to most imperative programming languages. We assume that the reader is familiar with the following: (1) Big Oh notation; (2) An imperative programming language; (3) Object oriented concepts.
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by Luc Devroye - Birkhauser
In these lecture notes, we attempt to explain the connection between the expected time of various bucket algorithms and the distribution of the data. The results are illustrated on standard searching, sorting and selection problems.
by Sean Luke
This is an open set of lecture notes on metaheuristics algorithms, intended for undergraduate students, practitioners, programmers, and other non-experts. It was developed as a series of lecture notes for an undergraduate course.
by Wolfgang Merkle - ESSLLI
The first part of the course gives an introduction to randomized algorithms and to standard techniques for their derandomization. The second part presents applications of the probabilistic method to the construction of logical models.
by K. Mehlhorn, P. Sanders - Springer
This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, etc.