Learn and practice

Reference

Operation costs and implementation assumptions to use when comparing interview solutions. Keep the reference beside your practice exercises.

Reference

Data structure time complexity reference

Compare arrays, hash maps, linked lists, stacks, queues, trees, and heaps with worst-case, expected, and amortized costs explained.

Reference

Python collections for interviews: dict, Counter, deque, and heapq

Choose Python collections by operation, write counts and adjacency lists, and test queue, heap, missing-key, and copying behavior.

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Coding interview practice worksheet: contract, invariant, tests, and review

Use a printable problem-solving worksheet to clarify a contract, compare approaches, trace an invariant, select edge cases, and plan a concrete follow-up.

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Mock coding interview rubric with observable review criteria

Review clarification, correctness, reasoning, testing, complexity, and communication using observable evidence and specific follow-ups, without a fabricated hiring score.

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How to choose a data structure for an interview problem

Choose arrays, maps, sets, deques, heaps, trees, tries, and disjoint sets by required operations, order, identity, mutation, and cost assumptions.

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Interview collection operations across ten programming languages

Compare map presence, queues, copying, numeric boundaries, and text units across JavaScript, TypeScript, Python, Java, C++, C#, Go, Kotlin, Swift, and Rust.