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 Nashat Mansour - InTech
This book demonstrates the applicability of search algorithms for the purpose of developing solutions to problems that arise in a variety of domains. It is targeted to a wide group of readers: researchers, graduate students, and practitioners.
by Macneil Shonle, Matthew Wilson, Martin Krischik - Wikibooks
An accessible introduction into the design and analysis of efficient algorithms. It explains only the most basic techniques, and gives intuition for and an introduction to the rigorous mathematical methods needed to describe and analyze them.
by David M. Mount - University of Maryland
The focus is on how to design good algorithms, and how to analyze their efficiency. The text covers some preliminary material, optimization algorithms, graph algorithms, minimum spanning trees, shortest paths, network flows and computational geometry.
by Wojciech Szpankowski - Wiley-Interscience
A book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms.