New Mexico Computer Science For All

1. New Mexico Computer Science For All Sorting Algorithms Maureen Psaila-Dombrowski

2. Sorting • Sorting is something we do without even thinking about it. • Some one deals us a hand of cards -we put them in order • Empty the dishwasher – silverware goes one place, plates and glasses go to another…. • Sorting is arranging a group of things (set) according to some criteria: • Increasing/decreasing order • Size • Kind • Class • Brightness • Nearly anything that can describe the items

3. So What? • No big deal – just sort it! • But what about …

4. So What? • OR the phone numbers of everyone in US

5. Sorting in Computer Science • Sorting is extremely and increasingly important. • Data sets can be HUGE • Bring order to the mess • Need order to better access and use the data • Goal of Sorting in Computer Science • Given a set (container) of n elements • Figure out how to sort them (the criteria to use). • Create an Algorithm to sort them • Have the computer sort them!

6. Sorting Algorithms • Many types of sorting algorithms, a few are: • Insertion Sort • Bubble Sort • Merge Sort • Selection Sort • Quick Sort • Heap Sort • Shell Sort • Each has its place • Look at two of them (sort numbers in ascending order)

7. Insertion Sort • Commonly done by everyone • don’t think about it • Looks like: • Start with an Unsorted List (think of a hand of cards) • Take the first number  new Sorted List • Then • Take next number from Unsorted List • Put in its correct sorted place in the Sorted List • Keep doing that until entire Unsorted List is Sorted!

8. Insertion Sort - Example

9. Insertion Sort - Example

10. Insertion Sort - Example

11. Insertion Sort - Example

12. Insertion Sort - Example

13. Insertion Sort - Example

14. Insertion Sort - Example

15. Insertion Sort • Pros • Very simple to understand • Very simple to implement • Little memory needed • Efficient for small data sets • Cons • Takes a long time • Inefficient for large data sets • Requires a large number of operations (shifts) • O(n2)

16. Merge Sort • Commonly used by programmers • A Recursive, Divide and Conquer technique • Looks like: • Keep Dividing the unsorted list (recursive) • smaller and smaller lists • until you get nsublists, each containing 1 element • a list of 1 element is considered sorted • Keep Merge and Sort pairs of lists • compare the first element in each unsorted list and put the smallest into a new sorted list • each iteration creates larger lists • repeat until all lists are sorted.

17. Merge Sort - Example

18. Merge Sort - Example

19. Merge Sort - Example

20. Merge Sort - Example

21. Merge Sort - Example

22. Merge Sort - Example

23. Merge Sort • Pros • Takes less memory than other sorting methods • Takes less time than other sorting methods • O(n(logn)) • Cons • More difficult to understand • More difficult to implement

24. Summary • Sorting: arranging a group of things (set) according to some criteria (Increasing/decreasing order, Size, Kind…) • Sorting is extremely and increasingly important. • Many types of sorting algorithms • Insertion Sort: Commonly done by everyone • Very simple to understand and implement, Little memory needed, Efficient for small data sets • Takes a long time, Inefficient for large data sets, Requires a large number of operations (shifts), and is O(n2) • Merge Sort: Commonly used by Programmers • A Recursive, Divide and Conquer technique • Takes less time and memory than other sorting methods (O(n(logn)) • Somewhat more difficult to understand and implement