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Equation 12 · Part 4 · Why Average Success Rate Hides the Failures That Matter Most

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

The expressions on both sides represent the same quantity under the stated assumptions.

Its job in the formula

The equals sign connects the complete expression on the left with the complete expression on the right. Both sides must have compatible units.

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

An equals sign says that the expression on its left and the expression on its right have the same value under the stated definitions and assumptions.

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Sources cited in the surrounding passage

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