Practical Analysis Of Algorithms

This Book Introduces The Essential Concepts Of Algorithm Analysis Required By Core Undergraduate And Graduate Computer Science Courses, In Addition To Providing A Review Of The Fundamental Mathematical Notions Necessary To Understand These Concepts. Features: Includes Numerous Fully-worked Examples And Step-by-step Proofs, Assuming No Strong Mathematical Background; Describes The Foundation Of The Analysis Of Algorithms Theory In Terms Of The Big-oh, Omega, And Theta Notations; Examines Recurrence Relations; Discusses The Concepts Of Basic Operation, Traditional Loop Counting, And Best Case And Worst Case Complexities; Reviews Various Algorithms Of A Probabilistic Nature, And Uses Elements Of Probability Theory To Compute The Average Complexity Of Algorithms Such As Quicksort; Introduces A Variety Of Classical Finite Graph Algorithms, Together With An Analysis Of Their Complexity; Provides An Appendix On Probability Theory, Reviewing The Major Definitions And Theorems In The Book.