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Equation 12 · Part 5 · Why Average Success Rate Hides the Failures That Matter Most

multiplication

R=∑iPr⁡(failure mode i)⋅BiR = \sum_{i} \Pr(\text{failure mode } i) \cdot B_i
multiplication

What this part means

Multiply the quantities on either side.

Its job in the formula

Multiply the quantities on either side.

The passage around this formula

Finding the failure is only half the design problem. The other half is scoring it, and a plain pass/fail count throws away exactly the information a consequence-aware evaluation needs — it treats a wrong word choice and a deleted database as the same unit. A more defensible score weights each discovered failure mode by its consequence rather than counting it once: R=∑iPr⁡(failure mode i)⋅BiR = \sum_{i} \Pr(\text{failure mode } i) \cdot B_i. where BiB_i is the blast radius assigned to failure mode i : how much of a system, how much data, how many users or how much liability a given failure could plausibly reach, drawn from a small number of severity tiers rather than treated as a continuous unknown. This is not a hypothetical scoring scheme; tiered,…

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Learn the underlying idea

Multiplication scales one quantity by another. A dot, a cross, or adjacent symbols can indicate a product.

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Sources cited in the surrounding passage

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