Data Structures

Suffix Tree

A powerful data structure for advanced string processing, enabling linear-time solutions to complex substring problems.

Suffix Tree Conceptual Overview

Constructing a Suffix Tree in linear time is complex and typically involves advanced algorithms like Ukkonen's algorithm. Below is a simplified, conceptual implementation to illustrate the basic structure.

# Note: A production-ready Suffix Tree is highly complex.
# This is a simplified version for conceptual understanding.

class SuffixTreeNode:
    def __init__(self):
        self.children = {}

class SuffixTree:
    def __init__(self, text):
        self.root = SuffixTreeNode()
        text += '$'  # Add a unique terminator
        for i in range(len(text)):
            self.insert_suffix(text[i:])

    def insert_suffix(self, suffix):
        node = self.root
        for char in suffix:
            if char not in node.children:
                node.children[char] = SuffixTreeNode()
            node = node.children[char]

    def has_substring(self, substring):
        node = self.root
        for char in substring:
            if char not in node.children:
                return False
            node = node.children[char]
        return True

AI Coach Hint: While the above code demonstrates the idea of a trie of suffixes, a true Suffix Tree compresses paths, meaning nodes can represent sequences of characters, not just one. This compression is what makes them space and time-efficient. For interviews, understanding the applications and the high-level concept of Ukkonen's algorithm is more important than a full implementation.

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