Chapter 7 Lafores Book Advanced Sorting Hwajung Lee

Chapter 7 (Lafore’s Book) Advanced Sorting Hwajung Lee ITEC 324 Principle of CS III

Sorting Definition: Arrange items in a predetermined order. Summary. Sort. doc

Shellsort (1) The Shellsort is named for Donard L. Shell, the computer scientist who discovered it in 1959. Objective: To sort a sequence of numbers Method: Based on the insertion sort, but adds a new feature that dramatically improves the insertion sort’s performance.

Shellsort (2) Applet: Shell. Sort Diminishing Gaps Also called Interval sequence or gap sequence Time complexity of Shell sort depends mainly on the interval sequence Suggested interval sequence

Shellsort (6) Diminishing Gaps Interval sequence suggested by Knuth based on the following equation h = h*3 + 1 Known as the best interval sequence in terms of time complexity until now.

Shellsort (7) Diminishing Gaps You can try your own interval sequence.

Shellsort (8) Source Code of Shell. Short

Shellsort (9) Computational Performance No theoretical analysis. Based on experiment, O(N 3/2) ~ O(N 7/6)

Shellsort (10) Advantages Good for medium-sized arrays, perhaps up to a few thousand items. Much faster than O(N 2) sorts Very easy to implement – The code is short and simple Solves a problem of the insertion sort that it requires too many copies

Shellsort (11) Disadvantages Not quite as fast as quicksort and other O(N*log. N) sorts, so not optimum for very large files.

Quick Sort (1) Discovered by C. A. R. Hoare in 1962. The most popular sorting algorithm due to its efficiency. Objective: To sort a sequence of numbers Method: Based on partitioning data. Efficiency (time complexity): O(N*log. N) Applet: Quick Sort 1, Quick Sort 2

Quick Sort (2) Partitioning Using partitioning, data are divided into two groups such that all the items with a key value higher than a specified amount are in one group, and all the items with a lower key value are in another. pivot value it is the value used to determine into which of the to groups an item is placed. ( cf. key values: data which need to be sorted. )

Quick Sort (3) Partitioning Algorithm

Quick sort in details (4) Three basic steps: Textbook page 334 fig 7. 8 Partition the array or subarray into left(smaller keys) and right (larger keys) groups. call ourselves to sort the left group. call ourselves to sort the right group.

Quick sort (5) (Problem) If the data is already sorted (or inversely sorted) Degenerates to O(N 2) Performance (Solution) Median-of-Three Partitioning

Quick sort (6) Before sorting Left 44 center 86 right 29 median is 44 After sorting Left 29 center 44 right 86

Quick sort (7) In order to use the mechanism of the existing rec. Quick. Sort(), put the median at the rightmost cell. Left 29 center 86 Source Code of Quicksort version 2 right 44

Quick sort (8) [Handling Small Partitions] If you use the median-of-three partitioning method, the quicksort algorithm will not work for partitions of three or fewer items. Cutoff point 3 Cutoff point 9 is recommended by Knuth and considered where the best performance lies. But, it will depend on your computer, operating system, compiler (or interpreter), and so on. Revised Source Code of Quicksort version 2

Radix Sort Radix: a base of a system of numbers Algorithm of Radix Sort Time Complexity of Radix Sort: O(K(N+d)), where K = the number of digits in keys N = the number of key values (= the number of inputs) d = the number of radix