Why Do Computational Scientists Trust Their Software?
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Some of the feedback I got from the group:
- You could try looking at how defect rate changes over time. Use the trends as comparison points, or build a prediction model and then compare parameters of the model. (see ISSTA)
- Can you really investigate code quality separately from the concerns of model quality?
- How would you (well, the climate scientists) know a perfectly correct piece of software if they had one?
- The criticality of a defect has many dimensions.
- Consider code churn in estimation of code quality (high churn with low defects -> high quality process?). Or simply just making the churn data available might help ground the defect density data.
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