HW 8: Implementing a Heap
Solution
- MaxHeap.java : A max heap solution with the provided TopK.java file
- MinHeap.java : A min heap solution with a heapify constructor
- TopK.java : A TopK.java version to use a min heap plus with faster I/O
Overview
This is a programming homework assignment. It is due via ic312-submit
Due Date
This homework is due Mon. 14 Nov. at 2359
Grading
The assignment is graded out of 100 points. Deductions will be assessed based on the correctness and efficiency of your solution.
Starter Code
You will be provided with the following files in the base directory
example.txt
: an example set of inputsTopK.java
: a java class with a main method to find the Top K input
The following relevant files are found in the ic312
package.
MaxHeap.java
: Starter code for a max-heap implementation of a priority queue. You will need to edit this file.MinHeap.java
: Starter code for a min-heap. Complete this file for the Bonus!
Additionally, you will be provided with additional, useful data
structures in the ic312 directory. In particular, Pair.java
and
ArrayList.java
may be very useful!
Description
Overview
Modern road races are "chip-timed", which means that competitors can start and finish at different times, and the winner is not necessarily the person who crosses the finish line first.
Your task for this homework will be to complete the implementation of a program that reads in a whole bunch of names and times, and prints out the names of the top K finishers with the lowest times, where the value of K is specified as a command-line argument. To do that, of course, you will be completing the implementation of a Heap.
Details
The TopK.java
program is already written for you. It creates a
max-heap
, reads in all the names and times, calling removeMax
as necessary to maintain the heap size of K, and finally prints out
the contents of the heap to show the top K finishers.
You just need to fill in the ic312/MaxHeap.java
methods to
implement the Priority Queue.
Bonus! (Replace the lowest HW grade)
But wait, there is another way to do it! Instead of using a
max-heap, whose size is always at most K+1, you could instead
create one big min-heap with a "heapify" operation, then call
removeMin
K times to get the K smallest things. Instead of \(O(n
\log K)\), this way would only have running time \(O(n + K\log
n)\), which is potentially much better!
For this, you will create a min-heap instead of a max-heap. So your
TimeHeap class will have a removeMin operation instead of
removeMax. Oh, and you will also have to write a heapify
method,
and adjust the TopK.java program as necessary to make the
appropriate calls.
This is harder, so I provide an incentive: *If you do it this way with a min-heap, your lowest HW grade from the first 7 homeworks will be overwritten with this HW grade.*
The fastest program in the class wins a tangible prize. Are you up to the challenge? I hope so. Good luck!
Example Output
When everything works, if your program is run with java TopK 10
and then the following (found in example.txt
) is typed into standard in (followed by
ctrl-D):
Nathan 609601 Liam 707303 Logan 318344 Ethan 91286 Jacob 334328 William 631989 Samuel 592643 Sofia 492706 Sara 964558 Isabella 878226 Ava 613357 Emma 366389 Noah 60429 Emily 474105 Benjamin 645060 Chloe 481035 Lucas 502159 Maya 248729 Olivia 109154 Leah 28141
then the output should be
10. Chloe 9. Emily 8. Emma 7. Jacob 6. Logan 5. Maya 4. Olivia 3. Ethan 2. Noah 1. Leah
In fact, the example.txt file contains exactly this example, so for this one you could just run:
java TopK 10 < example.txt.
Note: Your code will be tested on more stringent examples than this using different test programs that make heaps larger than size 10. So you should test your own code like that as well!