Difference between revisions of "CSC212 Lab 12 2014"
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=Lab Problem #1= | =Lab Problem #1= | ||
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− | * Java | + | * Java provides ''heap'' data structures, but calls them ''PriorityQueues''. |
* Instead of keeping the largest element at the top of the heap, PriorityQueues keep the ''smallest'' elements at the top. | * Instead of keeping the largest element at the top of the heap, PriorityQueues keep the ''smallest'' elements at the top. | ||
* Try the example below to see how to use a [https://docs.oracle.com/javase/7/docs/api/java/util/PriorityQueue.html PriorityQueue] | * Try the example below to see how to use a [https://docs.oracle.com/javase/7/docs/api/java/util/PriorityQueue.html PriorityQueue] |
Revision as of 19:52, 9 November 2014
--D. Thiebaut (talk) 19:37, 9 November 2014 (EST)
Lab Problem #1
- Java provides heap data structures, but calls them PriorityQueues.
- Instead of keeping the largest element at the top of the heap, PriorityQueues keep the smallest elements at the top.
- Try the example below to see how to use a PriorityQueue
import java.util.PriorityQueue; public class HeapPriorityQueue { public static void main(String[] args) { PriorityQueue<Integer> heap = new PriorityQueue<Integer>(); heap.add( 1 ); heap.add( 20 ); heap.add( 5 ); heap.add( 100 ); while ( ! heap.isEmpty() ) System.out.println( heap.poll() ); } }
- Question 1
- Using some of the code/functions from this page, create a function called heapsort( int[] A ) that will use a priority queue to sort the array of ints A.
- Question 2
- Using the code snippet below, measure the execution times of QuickSort and of your HeapSort function. Figure out which is regularly faster on arrays of varying sizes.
long start = System.nanoTime(); quicksort(A, 0, A.length - 1); long end = System.nanoTime(); System.out.println( String.format( "quickSort( %d ) takes %1.3f msec", N, (end-start)/1000000.0f ) );