Problem Solving with Algorithms and Data Structures Using Python
by Brad Miller, David Ranum
Publisher: Franklin, Beedle & Associates 2011
Number of pages: 438
This textbook is designed to serve as a text for a first course on data structures and algorithms, typically taught as the second course in the computer science curriculum. We cover abstract data types and data structures, writing algorithms, and solving problems.
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by Herbert Edelsbrunner - Duke University
The main topics to be covered in this course are: Design Techniques; Searching; Prioritizing; Graph Algorithms; Topological Algorithms; Geometric Algorithms; NP-completeness. The emphasis will be on algorithm design and on algorithm analysis.
by Niklaus Wirth - Prentice Hall
The book treats practically important algorithms and data structures. It starts with a chapter on data structure, then it treats sorting algorithms, concentrates on several examples of recursion, and deals with dynamic data structures.
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 Jianer Chen
The author concentrates on four themes in computational geometry: the construction of convex hulls, proximity problems, searching problems and intersection problems. Solving manufacturing problems requires application of fast-algorithm techniques.