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Published equation contexts

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

Why this formula appears here

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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ii

Symbol i

i appears in the bound of this sum. The bound states where the repeated operation starts, ends, or which values it includes.

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BiB_i

Symbol B_i

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.

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Pr⁡\Pr

Probability operator

The probability operator gives the chance of the event named inside its brackets or parentheses.

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ii

Starting index or lower bound: i

This label says where the repeated addition, multiplication, or accumulation starts. Read its value or condition together with the article’s description of the index.

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Published contexts (1)

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

Equation 12 · Model Evaluation

Why Average Success Rate Hides the Failures That Matter Most

This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.

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,…

Meanings in this article

  • BiB_i: 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.
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