Bytedance·Machine Learning Engineer·Technical Phone Screen·Senior

Senior

Jul 2026

Summary

Bytedance ML engineer interview that was basically a deep dive into one coding problem. The question looked like a deque at first but the O(1) search requirement is what makes it actually hard.

Questions Asked (1)

Design a data structure backed by a fixed-capacity circular array that supports insert and remove at both ends, plus a search operation, all in O(1) time.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The push/pop stuff I had down pretty quick, circular buffer with head and tail indices is pretty textbook.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements: fixed capacity, O(1) insert/remove at both ends (deque), and O(1) search. Explain that a circular array with head/tail pointers gives O(1) ends, but O(1) search requires an auxiliary hash map from value to indices. Then discuss the trade-offs and implementation details.

Pro tip: Mention that the hash map must handle duplicate values by storing a set of indices per value, and that removal from the middle of the set is O(1) if using a doubly linked list or by swapping with the last element in the set. This shows you've thought about edge cases.

1. Clarify requirements and constraints

Confirm that 'search' means checking existence of a value, and that all operations must be O(1) on average. Ask about duplicate values and whether the array is fixed-size.

2. Design the circular array for ends

Use a fixed-size array with head and tail indices, and a size counter. Insert/remove at front/back adjust head/tail modulo capacity in O(1).

3. Add auxiliary hash map for O(1) search

Maintain a hash map from value to a set of indices where it appears. Update the map on every insert/remove. For duplicates, use a set (e.g., hash set) to allow O(1) add/remove.

4. Handle index updates on removal

When removing an element, remove its index from the set. If the set becomes empty, delete the key. For front/back removals, the index is known; for arbitrary removal (if needed), swap with last element to keep O(1).

5. Analyze complexity and trade-offs

All operations are O(1) average time, O(n) space. Discuss potential worst-case O(n) for hash collisions, and alternatives like balanced BST for O(log n) worst-case.

Key Points to Mention

Circular array with head/tail pointers and modulo arithmetic for O(1) insert/remove at both ends.
Auxiliary hash map from value to set of indices to achieve O(1) search.
Handling duplicates by storing multiple indices per value in a set.
Updating the hash map on every insert and remove to maintain consistency.
Space-time trade-off: O(n) extra space for O(1) search.
Average O(1) vs worst-case O(n) due to hash collisions; mention alternatives if strict O(1) worst-case is required.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.