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Array and String Manipulation Questions

Comprehensive coverage of language level operations and algorithmic techniques for arrays and strings that are commonly evaluated in coding interviews. Candidates should understand common language methods for arrays and strings, including their parameters and return values, chaining of operations, and the implications of mutable versus immutable types for in place versus extra space solutions. Core algorithmic patterns include iteration and traversal, index based and pointer based approaches, two pointer strategies, sliding window, prefix and suffix sums, sorting and partitioning, and cumulative or running sums. Problem classes include traversal, insertion and deletion, reversing and rotating, merging and deduplicating, subarray and substring search, anagram detection, palindrome detection, longest substring and maximum subarray problems, and pointer based reordering and partitioning tasks. Pattern matching techniques include naive matching, Knuth Morris Pratt and rolling hash approaches, and hashing for frequency and membership checks. String transformation and comparison topics include edit distance, sequence transformation problems such as word ladder, and parsing and validation tasks. Candidates should be prepared to implement correct and efficient solutions in common programming languages, reason about time and space complexity, optimize for input size and memory constraints, handle edge cases such as empty inputs and boundary conditions, and address character level concerns such as encoding differences, multibyte characters, surrogate pairs and unicode normalization. Interviewers may probe language specific implementation details, in place mutation versus copying, fixed buffer strategies, streaming or incremental algorithms for large inputs, and trade offs between clarity and performance. Expect questions that require selecting the right algorithmic pattern, implementing a robust solution, and justifying complexity and memory decisions.

EasyTechnical
46 practiced
Implement remove_element(nums, val) in-place in Python or Java: remove all occurrences of val from nums and return the new length. This is part of a backend cleanup job where payload arrays must be compacted before storage. Explain how to move elements and whether order must be preserved.
EasyTechnical
56 practiced
Implement string_to_int(s) (atoi) in Java or Python for backend input parsing: trim leading/trailing spaces, handle optional '+' or '-', parse digits until non-digit, and clamp to 32-bit signed integer range. Explain how you detect overflow without using big-integer libraries and how you treat invalid inputs.
HardTechnical
88 practiced
You need to design string key normalization and hashing for a backend user directory to ensure logically identical user-supplied strings compare equal. Discuss Unicode normalization (NFC vs NFD), case folding, trimming and canonicalization steps, and how to produce stable hashed keys for DB indexes. Also discuss security and collision considerations.
MediumTechnical
51 practiced
Implement merge_intervals(intervals) where intervals is a list of [start, end] pairs. This backend feature removes overlapping scheduled jobs by merging overlapping intervals. Provide an algorithm that sorts by start time and merges in one pass. Discuss closed vs open intervals and integer overflow for large timestamps.
HardTechnical
50 practiced
Given a string s, compute all palindrome partitions that achieve the minimum number of cuts (palindrome partitioning) for a backend content transformation service. Implement an algorithm that precomputes palindromic substrings and uses DP/backtracking to output partitions minimizing cuts. Discuss time/space complexity and pruning strategies.

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