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String Algorithms and Pattern Matching Questions

Covers algorithmic techniques and practical skills for solving string problems and pattern matching tasks. Core algorithm knowledge includes substring search and pattern matching algorithms such as Knuth Morris Pratt, Rabin Karp, Boyer Moore, Z algorithm, Aho Corasick for multiple pattern matching, and rolling hash methods. Data structures and suffix structures are important, including tries, suffix arrays, suffix trees, and suffix automata, together with longest common prefix arrays and related construction techniques. Also includes dynamic programming approaches for string problems such as edit distance and longest common subsequence, palindrome and anagram detection methods, and regular expression concepts and engine behavior. Emphasizes algorithmic complexity analysis, time and space trade offs, memory and streaming constraints, and optimization strategies for very long inputs and high throughput text processing. Practical considerations include parsing and string manipulation idioms in common languages, Unicode and character encoding issues, edge case handling, test case design for strings, and real world applications such as log analysis, text search, and data transformation.

HardSystem Design
0 practiced
Architect a distributed full-text search service for application logs with requirements: 50 TB of text, 100k queries/sec, <200ms latency, support for phrase search, wildcards, and scoring. Discuss indexing strategy (inverted index vs suffix structures vs n-grams), sharding, compression (posting lists), replication, update strategies, and how to support fuzzy matching at scale.
MediumTechnical
0 practiced
Describe and implement (or outline code) the doubling algorithm for suffix array construction (O(n log n)) in Python: iteratively sort suffixes by first 2^k characters using rank pairs (rank[i], rank[i+k]). Explain memory/time trade-offs compared to naive sort and SA-IS linear-time methods.
EasyTechnical
0 practiced
Write a Python function is_palindrome(s: str) -> bool that returns True if s is a palindrome, ignoring non-alphanumeric characters and case (e.g., 'A man, a plan, a canal: Panama'). Explain algorithmic complexity and discuss how you'd extend this check to a streaming API where characters arrive incrementally and memory is limited.
HardTechnical
0 practiced
Implement the Boyer-Moore string matching algorithm in Python including the bad-character and good-suffix heuristics. Your function should return all starting indices of matches and handle overlapping occurrences. Discuss average-case sublinear behavior and degenerate worst-case complexities.
MediumTechnical
0 practiced
Write a Python function count_palindromic_substrings(s: str) -> int that counts palindromic substrings using the center-expansion technique (O(n^2) worst case). Explain the algorithm and briefly discuss Manacher's algorithm and when you would prefer it (O(n) time).

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