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.

HardTechnical

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Implement a fixed-size memory pool allocator in C++ that provides O(1) allocation and deallocation for objects of the same size. Provide an interface allocate() and deallocate(ptr), describe free list management, alignment, and discuss how to make it thread-safe with low contention.

EasyTechnical

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Compare separate chaining and open addressing (linear probing, quadratic probing, double hashing) for hash table collision resolution. Describe deletion, tombstones, load factor effects, clustering behavior, and which approach is more cache-friendly in practice.

HardTechnical

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Explain rank and select operations on bitvectors and implement a simple rank1(pos) and select1(k) interface using a two-level directory (superblocks and blocks) in C++ or pseudo-code. Discuss memory overhead and how to tune for speed vs space.

HardSystem Design

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Design an autocomplete service that returns top-K suggestions for a given prefix with strict latency requirements (e.g., < 50ms) and supports frequent updates to the candidate set (adds, deletes, weight changes). Describe the data structures (in-memory and on-disk), caching, sharding, and how to maintain accuracy under updates.

EasyTechnical

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Explain why appending to a dynamic array (for example std::vector in C++, ArrayList in Java) is considered amortized O(1). Include an explanation using either the accounting method or aggregate analysis, discuss the cost of resizing, the effect of different growth factors (e.g., 1.5x vs 2x), and memory overhead trade-offs in production systems.

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