How to think about Algorithms

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There are many algorithm texts that provide lots of well-polished code and proofs of correctness. This book is not one of them. Instead, this book presents insights, notations, and analogies to help the novice describe and think about algorithms like an expert. By looking at both the big picture and...

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Bibliographic Details
Main Author: Jeff Edmonds
Format: Printed Book
Published: Cambridge ; New York Cambridge University Press 2008
Subjects:
Study and teaching, Invariants, Algorithms, Loops (Group theory), Recursion theory
Table of Contents:
  • Iterative algorithms: measures of progress and loop invariants
  • Examples using more-of-the-input loop invariants
  • Abstract data types
  • Narrowing the search space: binary search
  • Iterative sorting algorithms
  • Euclid's GCD algorithm
  • The loop invariant for lower bounds
  • Abstractions, techniques, and theory
  • Some simple examples of recursive algorithms
  • Recursion on trees
  • Recursive images
  • Parsing with context-free grammars
  • Definition of optimization problems
  • Graph search algorithms
  • Network flows and linear programming
  • Greedy algorithms
  • Recursive backtracking
  • Dynamic programming algorithms
  • Examples of dynamic programs
  • Reductions and NP-completeness
  • Randomized algorithms
  • Existential and universal quantifiers
  • Time complexity
  • Logarithms and exponentials
  • Asymptotic growth
  • Adding-made-easy approximations
  • Recurrence relations
  • A formal proof of correctness.

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