Why did the motion arrive short?
Compare the motion predicted by a simulator with a recorded trace.
The question
A toy cart starts at marker 0. The command is issued before the first window. The model predicts movement from the first window and assumes the same travel in every moving window.
| Value | |
|---|---|
| Time windows | 4 |
| Marker intervals per moving window | 3 |
| Target marker | 12 |
The windows are equal. The markers are invented grid positions.
“How would you compare the prediction with the recorded motion?”
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A strong answer, step by step
Open each step in turn. This is one strong answer, not the only one.
Step 1: Read the prediction
What would you do here? Open the move you’d make.
Say the observed cart reaches marker 12 because it received the command before the first window.
Tempting, but it misses something. The simulation treats command and movement as immediate. The recorded response still needs a check.
State the prediction and the start-of-motion assumption.
The strong move. The model needs all four windows of motion to reach the target on time.
See how a strong candidate says it
“Four moving windows at three intervals each reaches marker 12. That assumes the cart moves in the first window.”
Why it works: The model needs all four windows of motion to reach the target on time.
Step 2: Ask for both traces
What would you do here? Open the move you’d make.
Check the command and motion records on the same time base.
The strong move. That comparison can distinguish a delay before movement from a lower speed once the cart is moving.
Use the command log alone to count moving windows.
Tempting, but it misses something. A command timestamp does not show when the cart started moving.
See how a strong candidate says it
“I’d compare the command time with the first measured movement on the same clock.”
Why it works: That comparison can distinguish a delay before movement from a lower speed once the cart is moving.
Step 3: Account for the delay
The recorded trace stays at marker 0 through the first 2 complete windows. It moves 3 marker intervals in each of windows 3 and 4.
What would you do here? Open the move you’d make.
Separate the delayed start from the travel during movement.
The strong move. The trace changes the number of moving windows. Its observed travel per moving window still matches the toy model.
Assume it moved more slowly for all four windows.
Tempting, but it misses something. The trace shows two stationary windows and then three intervals per moving window.
See how a strong candidate says it
“Only two windows include movement, so the cart reaches marker 6 and is 6 short. It would reach marker 12 after 6 total windows if the same travel continued.”
Why it works: The trace changes the number of moving windows. Its observed travel per moving window still matches the toy model.
Step 4: Explain the model gap
What would you do here? Open the move you’d make.
Call six windows the verified travel time.
Tempting, but it misses something. Only four windows were observed. Six assumes the movement would continue at the same rate.
Give the controls and test owners the observed timing gap and ask for more evidence.
The strong move. The trace explains the observed shortfall and leaves the cause and repeatability open.
See how a strong candidate says it
“The toy model starts motion too soon for this trace. I’d show the command and motion times and ask which test conditions reproduce the delay.”
Why it works: The trace explains the observed shortfall and leaves the cause and repeatability open.
The answer, in short
- Decision
- Report a two-window delay in observed movement.
- Because
- Two moving windows reach marker 6 by the deadline. The simulation expects marker 12.
- What would change it
- Matched command and motion traces would show when the delay recurs.
Common traps
- Treating a command as measured motion.
- Presenting a projected target time as observed.
Check your answer
- I stated the motion assumption.
- I matched both time records.
- I computed the shortfall.
- I kept the projection conditional.
Last reviewed Nov 11, 2026