Strings Overview

This section contains documentation for string data structures optimized for text processing and string operations.

Available String Data Structures

Trie (Prefix Tree)

• Purpose: Efficient storage and retrieval of strings with shared prefixes
• Key Operations: Insert, search, prefix matching, autocomplete
• Use Cases: Autocomplete systems, spell checkers, IP routing tables
• Time Complexity: O(m) for most operations where m is string length

Suffix Tree

• Purpose: Compressed trie containing all suffixes of a text
• Key Operations: Pattern search, longest common substring, suffix operations
• Use Cases: Text indexing, bioinformatics, data compression
• Time Complexity: O(n) construction, O(m) pattern search

Suffix Array

• Purpose: Space-efficient alternative to suffix trees
• Key Operations: Pattern search, LCP computation, suffix enumeration
• Use Cases: Text processing, genome analysis, string algorithms
• Time Complexity: O(n log n) construction, O(m log n) pattern search

String Data Structures Applications

These data structures enable efficient implementations of:

• Pattern Matching: Find occurrences of patterns in text
• Autocomplete: Suggest completions based on prefixes
• Longest Common Substring: Find shared substrings between texts
• Text Indexing: Build searchable indexes for large text collections