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You have a data science pipeline with multiple steps. How can regression testing help ensure pipeline stability after updates?

hard📝 Application Q8 of 15
Testing Fundamentals - Testing Types and Levels

You have a data science pipeline with multiple steps. How can regression testing help ensure pipeline stability after updates?

ABy cleaning data before each run
BBy retraining models with new data only
CBy rerunning tests on outputs of each step to detect unexpected changes
DBy increasing model complexity
Step-by-Step Solution
Solution:

  1. Step 1: Understand pipeline regression testing

    Regression tests rerun checks on outputs to catch changes after updates.

  2. Step 2: Eliminate unrelated options

    Retraining, cleaning, or increasing complexity are not regression testing methods.

  3. Final Answer:

    By rerunning tests on outputs of each step to detect unexpected changes -> Option C

  4. Quick Check:

    Regression testing = verify outputs unchanged [OK]
Quick Trick: Test outputs after changes to catch regressions [OK]
Common Mistakes:
  • Confusing regression testing with retraining
  • Thinking cleaning is testing
  • Assuming complexity helps testing

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