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Advanced Data Structures and Implementation Questions

Deep and practical expertise in advanced data structures, their implementation details, performance characteristics, and selection for both algorithmic problems and production systems. Topics include arrays and dynamic arrays, strings, linked lists, stacks and queues, hash tables, heaps and priority queues, various tree forms including binary search trees and balanced trees, tries or prefix trees, segment trees and binary indexed trees or fenwick trees, union find or disjoint set union, suffix arrays, and advanced graph representations. Candidates should be able to implement core structures from first principles, demonstrate interfaces and invariants, reason about insertion deletion search traversal and iteration costs including worst case average case and amortized analysis, and discuss memory management and ownership in low level languages such as C and C plus plus as well as safe memory and reference use in managed languages. Evaluation also covers trade offs between contiguous and pointer based layouts, cache friendliness, concurrency considerations, selection of structures based on access patterns update frequency and memory constraints, handling of edge cases, testing and performance tuning for realistic inputs, and applying structures to problems such as top K queries prefix search connectivity range queries caches and union operations.

MediumTechnical
0 practiced
You must support range minimum queries over a time series with frequent updates. Decide between segment tree, sparse table, and Fenwick tree for this workload, justify your choice, and explain algorithmic complexity and practical implementation considerations for each option.
MediumTechnical
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Implement a Trie (prefix tree) in Python that supports insert(word), delete(word), and count_prefix(prefix) returning how many inserted words share the prefix. Make your implementation memory-efficient and ensure delete cleans up nodes with zero children to free memory.
MediumTechnical
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You manage a feature store that must support prefix lookups for millions of string keys with frequent reads and occasional writes. Choose between a trie, hash table, or sorted array with binary search. Justify your selection for read latency, memory usage, and write/update complexity, and describe caching strategies for common prefixes.
HardTechnical
0 practiced
Propose and implement (or describe algorithmically) transformations to improve cache locality for pointer-based binary tree traversals, such as the van Emde Boas (vEB) layout. Explain how you map nodes to an array, why locality improves, and trade-offs when the tree is updated frequently.
HardTechnical
0 practiced
Implement a lock-free multi-producer multi-consumer (MPMC) queue in C++ and explain how you ensure safe memory reclamation for nodes (e.g., hazard pointers or epoch-based reclamation). Provide code sketches for enqueue/dequeue and explain the ABA problem and mitigations.

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