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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.

MediumSystem Design
55 practiced
Implement an algorithm to find the top-k most frequent strings from a large log file on a mobile device with limited memory. You may stream the file; propose an approach and code sketch (Java/Kotlin) that balances accuracy, memory, and battery use. Consider approximate algorithms if needed.
EasyTechnical
53 practiced
Given an array of n distinct integers in the range [0, n], one number is missing. Implement an algorithm in Java to find the missing number using constant extra space and linear time. Signature: int missingNumber(int[] nums). Explain how this XOR trick helps prevent integer overflow on mobile devices with limited 32-bit integers.
HardTechnical
61 practiced
Implement the 'Word Ladder II' variant: return all shortest transformation sequences from start to end. Discuss algorithmic design with performance and memory constraints on mobile, and sketch a Kotlin/Java solution that uses BFS to build layers and backtracking to reconstruct paths. Address how to limit explosion of paths on-device.
MediumTechnical
65 practiced
You need to deduplicate an unsorted array of strings while preserving the first occurrence order for a memory-constrained Android app. Implement a Kotlin solution: fun dedupePreserveOrder(arr: Array<String>): Array<String>. Discuss time/space trade-offs and an approach if available memory is too small to hold all unique keys at once.
MediumTechnical
65 practiced
Given a sorted array of integers, implement an efficient two-pointer method in Java to determine if there exists a pair that sums to a target value. Signature: boolean hasPairWithSum(int[] nums, int target). Explain why this is preferable on mobile to a hash-set-based approach for memory and power efficiency.

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