Head First Algorithms and Data Structures

Index

A

• adjacency lists, How to store a graph, How to represent Algorithm Land, Breadth-first search with an adjacency matrix, How the data structure impacts the complexity
• adjacency matrices, Representing a graph with an adjacency matrix, How the data structure impacts the complexity
• algorithms, Comparing Algorithms: A Recipe for Speed
  • and linked lists, Introducing linked lists
  • applying to arrays, Let’s talk about data structures
  • approximation, #6 Approximation algorithms
  • binary search, The second implementation
  • characteristics of, What is an algorithm, anyway?
  • criteria for, Being more precise
  • distributed, #4 Parallel and distributed algorithms
  • external memory, #8 External memory algorithms
  • for graphs, Another visit to Algorithm Land
    • (see also graphs)
  • greedy (see greedy algorithms)
  • in dynamic programming (see dynamic programming)
  • limits of, The Limits of Algorithms: The Edge of the Computable Universe
  • linear search, Looking at the code, The second implementation
  • parallel, #4 Parallel and distributed algorithms
  • performance efficiency and complexity (see Big O notation)
  • randomized, #9 Randomized algorithms
  • recursive, Thinking Recursively: Recursion
  • string, #5 String algorithms
  • time complexity, Introducing time complexity
    • (see also time complexity)
  • versus data structures, Time complexity of static array operations
• Amdahl’s Law, #4 Parallel and distributed algorithms
• amortized constant time (O(1)), Appending new items, Time complexity of dynamic array operations
• appending items in arrays
  • dynamic, What about dynamic ...