##### ###### ##### ### # # ### # # ###### ## ## ## ## ## ## ## # # # # # ## ##### #### ##### # # # # # # # #### ## # ## ## ## ## # # # # # ## ## # ###### ## ### # ### # ######
##### ###### ##### ### # # ### # # ###### ## ## ## ## ## ## ## # # # # # ## ##### #### ##### # # # # # # # #### ## # ## ## ## ## # # # # # ## ## # ###### ## ### # ### # ######
Tries store strings character by character, enabling O(L) operations on prefixes and words.
Why tries matter
Children for each character
Character by character
Following the path
The trie advantage
The foundational trie problem
Complete solution
Build your trie
Augmenting the trie
Removing words
Trie with wildcards
DFS for dot matching
Implement your solution
Trie + backtracking
Efficient multi-word search
Pruning and cleanup
Implement your solution
Trie with constraints
BFS on valid paths
Space optimization
Pattern matching powerhouse
Bitwise trie application
Numbers as bit strings
Implement your solution
Top-k suggestions
Trie with rankings
Implement your solution
Trie for dictionary lookup
Find shortest prefix match
Implementation trade-offs
Reducing space usage
When to use which
Suffix trie application
Test your understanding
What you learned
Classic 01-trie for maximum XOR queries. Insert, delete, and find max XOR with given number.
Prefix XOR with binary trie. Maximize XOR of prefix and suffix using 01-trie queries.
01-trie with counting. Count elements where XOR with x is less than threshold.
Binary search with trie-like state tracking. Understand prefix properties in sequences.
String manipulation with prefix/suffix matching. Trie-like thinking for palindrome construction.
Monotonic stack with XOR. Combines stack technique with binary representation analysis.
XOR subsequence problem. Use prefix XOR with set to track achievable values.
Coordinate queries with trie-like structure for nearest neighbor in specific direction.
Minimize inversions after XOR. Binary trie to count inversions at each bit level.
Segment tree with merge properties. Trie-like divide for range maximum queries.
Count distinct substrings with constraints using trie. Classic string trie application.
Find string appearing as prefix, suffix, and middle. Z-function or trie approach.
Fundamental trie implementation. Insert, search, and startsWith operations.
Trie with wildcard search using DFS. Handle '.' matching any character.
Trie + DFS on grid. Find all words from dictionary in board. Prune with trie prefixes.
Binary trie for maximum XOR. Greedy bit-by-bit selection using trie traversal.
Replace words with shortest root in dictionary. Classic trie prefix matching.
Find longest word buildable character by character. Trie with valid word marking.
Autocomplete with trie. Return top 3 lexicographically smallest matches per prefix.
Trie storing sums at nodes. Sum values of all keys with given prefix.
