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 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.
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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.
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