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

Discuss trade-offs between contiguous (array-based) and pointer-based layouts for large data structures in terms of cache performance, fragmentation, allocation overhead, prefetching, memory locality, and traversal speed. Give concrete examples where contiguous layout wins and where pointer-based structures are preferable in a data-engineering workload.

HardTechnical

0 practiced

Explain the SA-IS suffix array construction algorithm at a level that would allow implementation and discuss why it runs in linear time. Describe classification of S/L types, LMS substrings, induced sorting, and memory optimizations appropriate for very large strings in production text processing.

EasyTechnical

0 practiced

Explain disjoint-set union (union-find). Describe naive union-find, union by rank/size, path compression, and state the amortized complexity of operations. Give a concrete example of using union-find to compute connected components in a large graph as part of a data processing job.

MediumTechnical

0 practiced

Implement an open-addressing hash map with linear probing in C. Support put(key:string, value:int), get(key), delete(key), and resizing. Discuss tombstone handling for deletes, choosing load factor thresholds, using power-of-two table sizes for fast masking, and memory layout choices to be cache-friendly.

HardTechnical

0 practiced

Explain succinct data structures relevant to indexing: bitvectors with rank/select, wavelet trees, and FM-index. Describe how rank/select are implemented (sampling and popcount intrinsics), typical space/time trade-offs, and typical use-cases in compressed text indexing for large corpora.

Unlock Full Question Bank

Get access to hundreds of Advanced Data Structures and Implementation interview questions and detailed answers.

Join thousands of developers preparing for their dream job.