benchmarking
3 free lessons tagged benchmarking across Programming, Robotics. Each one is a short sequence of focused steps with narration and a five-question quiz at the end — take them in any order, no signup required.
Benchmarks That Hold Up, and Knowing When to Stop
A benchmark is an experiment, and most are badly designed enough to produce confident wrong answers. This lesson covers what a measurement must control to mean anything, the ways microbenchmarks lie including code the compiler deletes, how to catch regressions in continuous integration despite noisy machines, and how to recognise the point where optimising stops paying.
Measure First: The Arithmetic That Decides What to Optimise
Most optimisation effort is spent on code that was never the problem, and the reason is that intuition about where time goes is reliably wrong. This lesson covers why guessing fails, the arithmetic that caps what any optimisation can buy, the difference between latency and throughput, and how to set a target that tells you when to stop.
Why the Standard Metrics Mislead
Displacement error is the field's default metric and it rewards the wrong behaviour: hedged average predictions, physically impossible trajectories, and best-of-many reporting that flatters diverse nonsense. What to measure instead.