Pattern Searching

Pattern searching algorithms are essential tools in computer science and data processing. These algorithms are designed to efficiently find a particular pattern within a larger set of data.

Important Pattern Searching Algorithms:

• Naive String Matching : A Simple Algorithm that works in O(m x n) time where m is the length of the pattern and n is the length of the text.
• Knuth-Morris-Pratt (KMP) Algorithm It preprocesses pattern and works in O(m + n) Time.
• Rabin-Karp Algorithm : It uses hashing to compare the pattern with the text. It works in O(m x n) Time in worst case,
• Aho-Corasick Algorithm : A deterministic finite automaton (DFA) based algorithm and works in O(m + n) time.

Learn Basics of Pattern Searching:

• Introduction to Pattern Searching
• Naive Pattern Searching

Standard Pattern Searching Algorithms:

• Rabin-Karp Algorithm
• KMP Algorithm
• Z algorithm
• Finite Automata
• Boyer Moore – Bad Character Heuristic
• Aho-Corasick Algorithm
• Suffix Array
• Kasai’s Algorithm for LCP array from Suffix Array
• Online algorithm for checking palindrome in a stream
• Manacher’s Algorithm
• Ukkonen’s Suffix Tree Construction – Part 1
• Generalized Suffix Tree

Practice Problems on Pattern Searching:

• Frequency of a Substring
• Anagram Substring Search
• Check if Two Strings Rotations
• Substrings with all Vowels
• Substrings with only Given Character
• Find all Occurrences of a Subarray
• Pattern Searching using a Trie of all Suffixes
• Wildcard Pattern Matching
• Regular Expression Matching
• Longest prefix which is also suffix
• Count string in a 2D array
• Find all the patterns of “1(0+)1”
• Max length prefix as Subsequence
• Search a Word in a 2D Grid
• Word Search with Zig-Zag
• Suffix Tree Application 1 – Substring Check

Applications of Pattern Searching

Pattern searching algorithms have numerous applications, including:

• Text Processing: Searching for keywords in a document, finding and replacing text, spell checking, and plagiarism detection.
• Information Retrieval: Finding relevant documents in a database, web search, and data mining.
• Bioinformatics: Searching for DNA sequences in a genome, protein analysis, and gene expression analysis.
• Network Security: Detecting malicious patterns in network traffic, intrusion detection, and malware analysis.
• Data Mining: Identifying patterns in large datasets, customer segmentation, and fraud detection.

Recommended:

• Learn Data Structure and Algorithms | DSA Tutorial
• Practice problems on Pattern Searching