Question: Why does swapping the execution order of two independent components in a DAG-ordered pipeline (e.g., 'Detect pedestrians' and 'Detect cars') still result in valid error attribution analysis, despite potential minor changes in numerical results? Discuss in terms of DAG constraints and decision guidance.

Sample answer: Swapping independent components can slightly change the numerical error attribution because the exact ordering (such as A->B->C vs B->A->C) influences which component is evaluated first for specific failures. However, because both detection components do not depend on each other, the pipeline still conforms to a DAG ordering where later components (like path planning) rely only on earlier outputs. Consequently, the relative significance of each component remains clear, ensuring the error analysis provides correct guidance on where to focus optimization resources.

Key points:

• Swapping independent components preserves the core DAG dependency requirement.
• Order changes can slightly alter numerical metrics due to the order in which faults are attributed.
• The overall qualitative guidance on where to focus attention remains valid.

Rubric: The answer must mention that swapping independent components preserves the DAG ordering (later components depend only on earlier outputs). It must explain why numerical results might change slightly (due to changes in evaluation order). It must conclude that the analysis remains valid and continues to offer good guidance for prioritizing model development.