Arrays and Hash Map Operations Questions

Covers algorithmic patterns that use arrays together with hash based maps or dictionaries to achieve efficient lookup and counting. Topics include frequency counting, duplicate detection, two sum and k sum variants, sliding window with counts, index mapping, grouping by keys, and using hash maps to reduce time complexity from quadratic to linear. Emphasize insertion deletion and lookup costs, collision and memory considerations, trade offs between using hash maps versus sorting or two pointer techniques, and typical interview problem families that rely on combining arrays with associative containers.

MediumTechnical

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Implement an LRU cache class in Python with get and put operations that run in O(1) time. Use a hash map combined with a doubly linked list. Explain how this design supports high-throughput lookups in an ingestion service and outline thread-safety considerations.

EasyTechnical

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Given an array of unique keys representing partition IDs, build a mapping from key to index in Python to support constant-time lookups. Implement membership and index query functions and describe the time and space cost and how you would persist or serialize this mapping for fast startup.

MediumTechnical

0 practiced

Given an integer array and integer k, implement a Python function to count the number of continuous subarrays whose sum equals k using prefix sums and a hash map to store prefix sum frequencies. Explain why initializing the map with prefix 0 -> 1 is necessary and discuss integer overflow considerations.

EasyTechnical

0 practiced

Write a Python function that counts unique unordered pairs (i,j) in an integer array such that abs(nums[i] - nums[j]) == k. Use a hash-based approach to achieve expected O(n) time. State assumptions about duplicates and how you treat pair uniqueness.

MediumTechnical

0 practiced

Implement a function in Python that finds all unique triplets in an integer array that sum to zero. Discuss trade-offs between sorting + two-pointer approach and hash set approaches with respect to time, memory, and handling duplicates. Provide complexity analysis.

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