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 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 Jurg Nievergelt, Klaus Hinrichs - Prentice Hall
Contents: Programming environments for motion, graphics, and geometry; Programming concepts - beyond notation; Objects, algorithms, programs; Complexity of problems and algorithms; Data structures; Interaction between algorithms and data structures.
by Clifford A. Shaffer - Virginia Tech
A comprehensive treatment of fundamental data structures and algorithm analysis with a focus on how to create efficient data structures and algorithms. Aims to help the reader gain an understanding of how to select or design the best data structure.
by James Aspnes - Yale University
Topics include programming in C; data structures (arrays, stacks, queues, lists, trees, heaps, graphs); sorting and searching; storage allocation and management; data abstraction; programming style; testing and debugging; writing efficient programs.