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

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Presentation on theme: "New Mexico Computer Science For All Search Algorithms Maureen Psaila-Dombrowski."— Presentation transcript:

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

2 Search Algorithms Searching is what we when we want to find specific item among a group of items. Computer Science Problem  You have a list  You want to find a specific item - specify it  Use a Search Algorithm to find it Two algorithms  Linear (Sequential) Search  Binary Search

3 Linear (Sequential) Search Simplest search method Method: Check every one of its elements, one at a time and in sequence, until the desired one is found Psuedocode ▫Specify the item you are looking for ▫For each item in the list:  Check list item to see if it is desired item  YES  stop the search and return the item's location.  NO  go to the next item on the list

4 Linear (Sequential) Search 50539810………36525……… Here’s how it works….  Have a list - 1000’s items long (numbers)  Looking for a specific number (25) 25

5 Linear (Sequential) Search Pros ▫Simple  easy to understand and implement ▫Works well for  Small lists  Single searches of unsorted lists Cons ▫More time consuming than other methods ▫The worst case search  number items in the list

6 Binary Search Problem is the same ▫Performed on sorted lists.  List is already arranged in some order  Lower to highest  Brightest to darkest  ….. Method:  Start with a sorted list  Repeat  Divide list in half  Check to see which half your item is in  Select that half

7 Example: Looking for 18 15182739426199 151827 39426199 151827 18 Is 18 = 39 ? Is 18 = 18 ?

8 Video Clip Malan, David J. (2013, September 7). Introduction to Computer Science, [Part of CS50/Week 0: Wednesday]. Retrieved from http://www.youtube.com/watch?v=FWLeB436j1o

9 Binary Search Pros ▫Powerful ▫Fast ▫Relatively easy to understand ▫Works well for large sorted data sets Cons ▫Must sort your list first ▫More difficult to implement

10 Comparison Number of Items Linear Search (Worst Case ) Binary Search (Worst Case) 10 4 100 7 1,000 10 10,000 14 100,000 17 1,000,000 20 1,000,000,000 30

11 Summary Search Algorithms  to find a item with specific properties among a group of items Linear (Sequential) Search – check every element, one at a time.  Simple  easy to understand and implement  Good for small lists or single searches of unsorted data  More time consuming - the worst case search = number items in the list. Binary Search – keep dividing the list in half and checking to see which half list your item is in until you find it!  Powerful and fast  Works REALLY well for large sorted data  Must sort you list first and more difficult to implement


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