Which option best describes the practice that ensures simulations yield comparable results across trials?

Which option best describes the practice that ensures simulations yield comparable results across trials?

• A. Running each trial with different, random configurations
• B. Removing version control to speed up runs
• C. Ad hoc changes between trials
• D. Reproducible simulations with version-controlled configurations and fixed scenarios.

Answer: (D)

Ensuring results are comparable across trials comes from keeping the input conditions and setup the same each time. By using reproducible simulations with version-controlled configurations and fixed scenarios, you lock in the exact parameters, data inputs, and execution steps for every run. This means any differences seen between trials arise from the phenomena you’re studying (such as stochastic behavior) rather than from changes in how the simulation was run. Version control preserves the configuration history so you can re-create the same setup later, and fixed scenarios ensure starting conditions don’t drift between trials. When you instead vary configurations, remove version control, or make ad hoc changes, you introduce extra variability that makes comparisons unreliable.

Ensuring results are comparable across trials comes from keeping the input conditions and setup the same each time. By using reproducible simulations with version-controlled configurations and fixed scenarios, you lock in the exact parameters, data inputs, and execution steps for every run. This means any differences seen between trials arise from the phenomena you’re studying (such as stochastic behavior) rather than from changes in how the simulation was run. Version control preserves the configuration history so you can re-create the same setup later, and fixed scenarios ensure starting conditions don’t drift between trials. When you instead vary configurations, remove version control, or make ad hoc changes, you introduce extra variability that makes comparisons unreliable.