Performance · interview question

What is the healthiest performance judgment around microbenchmarks?

Multiple choiceMediumchapter-16-curatedpremiumperformancemicrobenchmarks

python

import timeit

print(timeit.timeit("sum(values)", setup="values=list(range(1000))", number=1000))

Measure before optimizing, then change the part that actually dominates cost instead of guessing from style alone.Keep microbenchmarks implicit so the script stays short and hope the next engineer infers the rule.Delay clarity until production traffic reveals the edge case and then patch it under pressure.Solve the symptom with comments only and avoid changing the code shape around microbenchmarks.

Answer and explanation

Correct answer

A. Measure before optimizing, then change the part that actually dominates cost instead of guessing from style alone.

Why

Premature optimization is usually weaker than targeted optimization backed by measurement.

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What is the healthiest performance judgment around microbenchmarks?

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