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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.

HardTechnical
52 practiced
Design an algorithm to find all occurrences of a pattern of length m in a text stream allowing up to k mismatches (Hamming or edit distance). Explain Myers' bit-parallel algorithm when m fits in machine word and hybrid/block techniques when m exceeds word size. Discuss performance and practical limits.
MediumTechnical
52 practiced
You're deduplicating product names from multiple locales. Describe a robust preprocessing pipeline to canonicalize keys for matching: encoding detection, Unicode normalization (NFC), case-folding, trimming, removing diacritics, whitespace normalization, and locale-sensitive rules. Explain potential false-merge trade-offs and how you'd test the pipeline.
EasyTechnical
61 practiced
Explain the key idea behind the Knuth-Morris-Pratt (KMP) algorithm for substring search. Describe how the prefix-function (failure function) is computed and used during search. Given pattern 'ababaca', compute the prefix-function array. Discuss time and space complexity and when KMP is a good choice compared to other matching methods.
HardTechnical
63 practiced
Behavioral: You're the data-science lead and a deployed text-matching pipeline has started missing high-priority alerts in production. Describe step-by-step how you'd triage the incident: scope impact, collect logs/metrics, establish mitigation (rollback/kill-switch), coordinate engineers and ops, prioritize fixes vs temporary workarounds, and prepare stakeholder communication and a post-mortem with preventive actions.
EasyTechnical
60 practiced
Explain the difference between NFA-based and DFA-based regular expression engines. Discuss how features like backreferences and capture groups impact implementation and performance. Provide an example regex that can cause exponential backtracking in an NFA engine and explain why.

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