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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.

HardTechnical
64 practiced
Describe algorithms to compute the number of distinct substrings of a string. Provide the O(n^2) naive approach and then explain how suffix arrays or suffix automata achieve O(n) or O(n log n) solutions. Outline how you'd implement and test the suffix-array-based approach for large inputs.
EasyTechnical
46 practiced
Write a JavaScript function to determine whether two strings are anagrams of each other. Consider case-insensitive comparison and assume Unicode input. Return true if they are anagrams (same character counts), false otherwise. Discuss time and space complexity and how to handle large input efficiently.
HardTechnical
66 practiced
Implement a function in Python that reorders a string so that no two adjacent characters are the same. If it's impossible, return an empty string. Aim for an approach using a max-heap (priority queue) of character counts and greedy selection. Example: 'aaabbc' -> 'ababac' (any valid reorder). Analyze time/space complexity.
MediumTechnical
44 practiced
Implement a JavaScript function to validate whether a given string is a valid IPv4 or IPv6 address. For IPv4, each octet should be 0-255 with no leading zeros unless the octet is zero; for IPv6, validate eight groups of 1-4 hex digits, allowing shorthand '::' once. Discuss edge cases and complexity.
EasyTechnical
64 practiced
Given a sentence as a string, implement a function in Python that reverses the order of words. For input 'the sky is blue' return 'blue is sky the'. Trim extra spaces so multiple spaces between words become single spaces in output, and remove leading/trailing spaces. Discuss in-place vs new-string approaches.

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