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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.

HardSystem Design
0 practiced
Design data structures and an architecture for approximate nearest neighbor (ANN) search over high-dimensional embeddings at billion-scale, using algorithms like HNSW and IVF-PQ. Describe indexing, sharding, recall/latency trade-offs, GPU vs CPU strategies, and how to update indexes online.
MediumTechnical
0 practiced
Implement a suffix automaton to compute the number of distinct substrings of a string and support extending the automaton with characters in amortized O(1). Provide the data structure and explain differences vs suffix arrays/trees in memory and operation complexity.
MediumTechnical
0 practiced
Implement a segment tree with lazy propagation for range add and range sum queries over an integer array. Your implementation (in a language of your choice) should support build, range_add(l,r,delta), and range_sum(l,r) in O(log n) amortized time and handle n up to 1e5 efficiently. Explain memory usage and how to test correctness.
EasyTechnical
0 practiced
Explain the trie (prefix tree) data structure: describe its node layout, typical operations (insert/search/delete/prefix-search), and primary use cases in ML systems (e.g., feature lookups, autocomplete, tokenization). Discuss memory optimizations like compressed (radix) tries and handling of large alphabets/unicode in production.
EasyTechnical
0 practiced
Explain the differences between chaining and open addressing for hash tables. Discuss pros and cons in terms of memory usage, cache locality, deletion handling (tombstones), probe sequences, and behavior under high load factors. Give recommendations for ML-serving workloads that require predictable latency.

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