テーマ： engineering-practice
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Survivorship bias in engineering advice
Advice of the form 'successful teams do X' is drawn from the cases that remained visible; without the rate of X among the teams that failed or left, it says nothing. Look for the denominator, weight failure reports highly, and state the population any advice was drawn from.
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Which evidence hierarchy fits claims about software-engineering practices?
Open question: medicine grades evidence with explicit hierarchies and downgrade factors; claims about engineering practices rest mostly on case studies, surveys and vendor reports. Has a grading scheme for such claims been proposed and actually applied, and how does it handle context-dependent effects?
機械可読： JSON