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sierra·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Had a coding round at Sierra for a Software Engineer role. Pretty focused on streams and iterators, with a follow-up that pushed into system design territory faster than I expected.

Questions Asked (1)

Q1

Design a class MultiplesStream(k) where each call to next() returns the next multiple of k in ascending order (k, 2k, 3k, and so on). Then extend it to handle multiple base integers, merging all their multiples in sorted order with no duplicates.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

The basic version was fine, just a counter times k, nothing to it.

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AI HintsAI Generated

Suggested Approach

Start by designing a simple MultiplesStream class that maintains a current value and increments by k on each next() call. For multiple base integers, use a min-heap to merge the streams, tracking the last emitted value to skip duplicates, and advance only the streams that produced the minimum.

Pro tip: Discuss the trade-offs between using a heap versus other approaches (like a priority queue with lazy deletion) and mention how to handle large k or many streams efficiently. Also, clarify whether the stream should be infinite and how to handle overflow.

1. Clarify requirements

Ask about constraints: number of base integers, range of k, memory limits, and whether duplicates should be skipped globally or per stream. Confirm that next() should return the next multiple in ascending order.

2. Design single stream

Implement MultiplesStream(k) with a current variable initialized to k, and next() returns current and then adds k. This is O(1) time and O(1) space.

3. Extend to multiple streams

Use a min-heap to store the next multiple from each base integer. Initially push each base integer. On next(), pop the smallest, record it as the result, and push the next multiple for that base (i.e., add the base to the popped value).

4. Handle duplicates

Keep track of the last emitted value. When popping from the heap, if the value equals the last emitted, skip it and push the next multiple for that base. Repeat until a new value is found.

5. Analyze complexity and edge cases

Time per next() is O(log m) where m is the number of base integers, due to heap operations. Space is O(m). Discuss edge cases: k=0 (infinite zeros?), negative k, overflow, and large m.

Key Points to Mention

  • Min-heap for merging sorted streams
  • Duplicate skipping using last emitted value
  • Time complexity O(log m) per next() for m streams
  • Space complexity O(m)
  • Handling of edge cases like k=0 or negative k
  • Potential optimizations: lazy deletion, using a priority queue with deduplication

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