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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