• For this lab, we will reimplement the WordCounter interface using tries.
• Download the provided code.
• The code for these labs will be incorporated into the editor.wordcount package.
• The code includes the following files:
  • editor.wordcount package
    • Trie.java: An implementation of WordCounter using a trie.
      • This is one of two files you will modify.
      • Within the file, modify the following methods:
        • Implement get() to perform a retrieval from the trie. Return 0 if the word is not present.
        • Implement bump() to try to find the word in the trie. If the word is present, increase its count. If the word is not present, you will need to add it to the trie, adding one node per character that is not already there.
        • Implement dock() to try to find the word in the trie, and decrease its count if it is there. Otherwise, do nothing.
        • You will also need to implement the Iter class, which represents a trie iterator. You'll want to use a stack to keep track of which Trie object is the next to be visited by the iterator.
    • TrieListSorted.java: An implementation of a sorted list of Trie objects.
      • This is one of two files you will modify.
      • It is used in the Trie class to represent a list of children of the current node.
      • This list is sorted based on the getChar() value for each Trie object.
      • Within the file, modify the following methods:
        • Implement insert() to insert a Trie into the list. This should maintain the sorted ordering, based on getChar().
        • Implement get() to retrieve a Trie from the list. This should use binary search.
    • TrieTest.java: Unit tests for Trie.java.
    • TrieTestRevised.java: Revised unit tests for Trie.java.
    • TimeTest.java: Program that compares the running times of different WordCounter implementations using Moby Dick. This version includes a test for our hash table implementation, so as to compare it to the others.
• Once your solution is working, run TimeTest to compare its performance with the sorted-array version from Lab 10 and the hash table from Lab 11.

Grading