Design a Recoverable Iterator
Company: xAI
Role: Software Engineer
Category: Coding & Algorithms
Difficulty: medium
Interview Round: Technical Screen
Quick Answer: This question evaluates data-structure and state-management skills, focusing on iterator semantics, snapshotting/restore mechanics, and efficient time-space trade-offs.
Part 1: Simulate a Recoverable Iterator for an In-Memory Collection
Constraints
- 0 <= len(items) <= 200000
- 1 <= len(operations) <= 200000
- All `restore` tokens are valid and were produced by an earlier `save` operation.
- Item values fit in 32-bit signed integers.
Examples
Input: ([1, 2, 3], [('save',), ('next',), ('next',), ('save',), ('restore', 0), ('next',), ('restore', 1), ('hasNext',), ('next',), ('next',)])
Expected Output: [0, 1, 2, 1, None, 1, None, True, 3, None]
Explanation: Two snapshots coexist. Restoring token 0 returns to the start, and restoring token 1 later still works.
Input: ([7, 8], [('save',), ('next',), ('hasNext',), ('restore', 0), ('next',), ('next',), ('hasNext',)])
Expected Output: [0, 7, True, None, 7, 8, False]
Explanation: Restoring the initial state lets the iterator replay the list from the beginning.
Input: ([], [('hasNext',), ('next',), ('save',), ('restore', 0), ('next',)])
Expected Output: [False, None, 0, None, None]
Explanation: Empty input should report no next element, and restoring the initial empty state changes nothing.
Input: ([5], [('next',), ('save',), ('hasNext',), ('restore', 0), ('hasNext',), ('next',)])
Expected Output: [5, 0, False, None, False, None]
Explanation: Saving after consuming the only element creates an end-state snapshot; restoring it keeps the iterator at the end.
Hints
- For an array-backed iterator, a snapshot only needs to remember the current index.
- Restoring a snapshot should not delete it; multiple saved states must keep working independently.
Part 2: Simulate a Recoverable Iterator on a Stream with Minimal Buffering
Constraints
- 0 <= len(stream) <= 200000
- 1 <= len(operations) <= 200000
- All `restore` and `release` tokens are valid and come from earlier `save` operations.
- A token is never released twice, and `restore` is only called on unreleased tokens.
- Stream values fit in 32-bit signed integers.
Examples
Input: ([10, 20, 30], [('save',), ('next',), ('next',), ('save',), ('restore', 0), ('next',), ('release', 0), ('next',), ('release', 1)])
Expected Output: ([0, 10, 20, 1, None, 10, None, 20, None], 2)
Explanation: Because snapshot 0 points to the beginning, the first two values must stay buffered until that snapshot is released.
Input: ([], [('hasNext',), ('next',), ('save',), ('restore', 0), ('release', 0)])
Expected Output: ([False, None, 0, None, None], 0)
Explanation: An empty stream never stores any buffered data.
Input: ([5, 6], [('next',), ('hasNext',), ('next',), ('hasNext',)])
Expected Output: ([5, True, 6, False], 0)
Explanation: With no saved states, each consumed stream element can be discarded immediately, so the retained buffer size stays 0.
Input: ([1], [('save',), ('next',), ('save',), ('restore', 0), ('next',), ('restore', 1), ('hasNext',), ('release', 0), ('release', 1)])
Expected Output: ([0, 1, 1, None, 1, None, False, None, None], 1)
Explanation: The first snapshot forces the single streamed value to stay buffered until token 0 is released; token 1 represents the end state.
Hints
- Unlike an array, a stream cannot be reread from the source. Any element that might be needed after a restore must stay in a buffer.
- Track the earliest unreleased snapshot position efficiently; a min-heap with lazy deletion works well.