Code Room
CodingEasycod-g1346
Subject Ml metricsLevel Entry–Mid~10 minCommon in ML systems interviewsIndustries Software development

Question

Two human annotators labeled the same batch of chat messages for a moderation training set, and the data lead wants to review every message they disagreed on. Given two equal-length lists of string labels, annotator_a and annotator_b, return the list of indices (0-based, in increasing order) where the two labels differ. Comparison is exact and case-sensitive. Example: annotator_a = ["ok", "toxic", "ok"], annotator_b = ["ok", "ok", "ok"] gives [1].

Implement
disagreement_indices(annotator_a: list[str], annotator_b: list[str]) → list[int]
Examples
in[["ok","toxic","ok"],["ok","ok","ok"]]out[1]
What a strong answer looks like

State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.

Vibe coding: describe the solution in plain language (or narrate it) and the coach grades your approach. Generating runnable code from your description is coming next.

Run or narrate your approach, then ask the coach.