This document provides code snippets and explanations for implementing a trie data structure for storing and searching words. It includes: 1. Code for adding a word to the trie by recursively traversing the trie and adding child nodes for each character in the word. 2. Methods for checking if a word is contained in the trie, and retrieving any word starting with a given prefix by traversing the trie down the prefix path. 3. Explanations of the trie node structure using a HashMap of children nodes indexed by character, and marking leaf nodes as containing a full word. 4. The trie allows fast dictionary lookups and prefix searches in O(L) time where L is the length of the query string.

1. Google
Applied CS
with Android

2. High Time

3. Ghost

4. How-to
1. Build dictionary
2. Set button click listeners
3. Decide the turn

5. Decide the turn
if (user's turn) {
listen to onKeyUp -> (k) {
if k is a valid letter {
append it to TextView
} else ignore
}
} else {
if word is of length 4 or more && it is a valid word {
Computer wins
} else {
put next character
}
}

6. Put next character
It should form a valid word
because this is a computer!

7. Ta-da !
while (low < high) {
mid = (low + high) / 2;
t = words.get(mid);
if(t.startsWith(prefix)) {
return t;
} else if(prefix.compareTo(t) > 0) {
// LHS is bigger
low = mid + 1;
} else {
// RHS is bigger
high = mid - 1;
}
}

8. Best case: O(1)
Average/Worst case:
O(log n)

11. Tri !
re(tri)eval

12. Basics
1. HashMap<Character, TrieNode> children
2. root.add(word)
3. root.isWord(word)
4. root.getAnyWordStartingWith(word)

13. Add a word to Trie
void add(String s, int position) {
if (position >= s.length()) return;
char c = s.charAt(position);
TrieNode n = children.get(c);
if (n == null) {
n = new TrieNode();
children.put(c, n);
}
if (position == s.length() - 1) {
n.isWord = true;
}
n.add(s, position + 1);
}

14. And a bit of method
overloading

15. void add(String s) {
add(s, 0)
}
void add(String s, int position) { ... }

16. Same logic, different application
1. root.isWord(word)
2. root.getAnyWordStartingWith(word)

17. Fast Dictionary !
An efficient lookup structure

18. This is it for today

19. Any doubts?