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temporal·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Temporal SWE interview with a log aggregation coding problem. Pretty focused on getting the implementation right under pressure, nothing wildly unexpected but the normalization detail was easy to fumble if you weren't paying attention.

Questions Asked (1)

Q1

Given a list of log entries where each entry has a timestamp, error code, link, and API name, produce an aggregated output grouped by unique (errorCode, API, normalized_link) tuples with occurrence counts. The normalization rule: replace every digit in the link with '#'.

Algorithms & Data StructuresSystem Design
Author's notes

The normalization part is where I almost tripped up.

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AI HintsAI Generated

Suggested Approach

Clarify the input format and expected output, then outline a solution that normalizes each link by replacing digits with '#', constructs a composite key from (errorCode, API, normalized_link), and uses a hash map to count occurrences. Discuss time and space complexity, and consider edge cases like empty input or non-string links.

Pro tip: Mention that normalization should be done once per entry and cached to avoid redundant work, and that using a delimiter unlikely to appear in the fields (e.g., '\u0000') prevents key collisions when concatenating.

1. Clarify requirements and constraints

Ask about input size, whether timestamps matter, and the exact output format (e.g., list of tuples with counts). Confirm that normalization applies only to digits in the link.

2. Design normalization and key construction

For each log entry, replace every digit in the link with '#' using a regex or character scan. Form a composite key from errorCode, API, and normalized link, using a delimiter to avoid ambiguity.

3. Aggregate counts with a hash map

Iterate through entries, compute the key, and increment its count in a hash map. This gives O(n) time and O(k) space where k is the number of unique keys.

4. Produce and format output

Convert the hash map into the required output structure, e.g., a list of objects or tuples containing the three fields and the count. Ensure ordering if specified.

5. Analyze complexity and edge cases

State time and space complexity, and discuss handling of empty input, null fields, or very large links. Mention potential optimizations like streaming aggregation.

Key Points to Mention

  • Normalization via regex or character replacement, ensuring only digits are replaced.
  • Composite key construction with a safe delimiter to prevent collisions.
  • Hash map for O(1) average-time aggregation, leading to O(n) overall time.
  • Space complexity O(k) where k is the number of unique tuples.
  • Edge cases: empty list, missing fields, non-string links, and links with no digits.
  • Potential for parallelization or streaming if data is large, though not required for basic solution.

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