Data Abstraction and Problem Solving with JAVA Walls and Mirrors Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Data Abstraction and Problem Solving with JAVA: Walls and Mirrors Carrano / Prichard Algorithm Efficiency and Sorting

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.1 Time requirements as a function of the problem size n

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.2 When n ≥ 2, 3 * n 2 exceeds n * n + 10

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.3a A comparison of growth-rate functions: a) in tabular form

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.3b A comparison of growth-rate functions: b) in graphical form

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.4 A selection sort of an array of five integers

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.5 The first two passes of a bubble sort of an array of five integers: a) pass 1; b) pass 2

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.6 An insertion sort partitions the array into two regions

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.7 An insertion sort of an array of five integers.

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.8 A mergesort with an auxiliary temporary array

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.9 A mergesort of an array of six integers

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.10 A worst-case instance of the merge step in mergesort

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.11 Levels of recursive calls to mergesort given an array of eight items

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.12 A partition about a pivot

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.13 kSmall versus quicksort

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.14 Invariant for the partition algorithm

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.15 Initial state of the array

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.16 Moving theArray[firstUnknown] into S 1 by swapping it with theArray[lastS1+1] and by incrementing both lastS1 and firstUnknown

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.17 Moving theArray[firstUnknown] into S 2 by incrementing firstUnknown

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.18a Developing the first partition of an array when the pivot is the first item

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.18b Developing the first partition of an array when the pivot is the first item

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.19 A worst-case partitioning with quicksort

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.20 A average-case partitioning with quicksort

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.21 A radix sort of eight integers

Data Abstraction and Problem Solving with JAVA Walls and Mirrors; Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Figure 9.22 Approximate growth rates of time required for eight sorting algorithms