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Lecture Structure
- Attributes 0f Dependability (00:00:01)
- Attributes 0T Dependability (00:01:41)
- 0n Dependability Attributes (00:03:53)
- Attributes 0t Dependability (00:06:56)
- Ability to undergo modifications (00:06:56)
- Wu W T (00:06:56)
- Confidentiality Absence of unauthorized disclosure of information (00:06:56)
- Instantaneous availability Probability that a system is performing (00:09:08)
- Reliability Function (00:09:08)
- Probability bf Events (00:13:55)
- Limits of integration depend the nature of the distribution function (00:15:59)
- Cumulative distribution function Probability that i t (00:15:59)
- Continuous variable Probability is in b (00:15:59)
- Probability bf Events (00:16:00)
- Cumulative distribution function Probability that M i (00:16:02)
- Continuous variable Probability that X is in b (00:16:02)
- Examples (00:21:59)
- The Reliability Function i Reliability Probability that a component (00:25:37)
- failure after t time to failure Reliability Function (00:25:37)
- failure before t Unreliability Function (00:25:37)
- Examples (00:26:52)
- Examples Probability that a component (00:27:09)
- failure after t time to failure Reliability Function (00:27:09)
- failure before t Unreliability Function (00:27:09)
- as random variable X (00:27:09)
- Idea Express time period of correct (00:27:09)
- Exponential (00:33:07)
- Distribution function that models the property Poisson process (00:33:07)
- Probability density function for random variable X (00:35:46)
- Examples (00:35:47)
- Reliability Function F Reliability Probability that a component (00:36:33)
- failure after t time to failure Reliability Function (00:36:33)
- failure before t Unreliability Function (00:36:33)
- as random variable X (00:36:33)
- Why Exponential (00:36:34)
- d Keynote Format H1 Q (00:39:17)
- d Keynote Format Q w N14 (00:39:23)
- Exponential (00:39:26)
- The Reliability Function P (00:39:32)
- Reliability function for exponential failure distribution (00:39:32)
- Failure m experience (00:39:32)
- Increasing probability of failure (00:39:32)
- The Reliability Function (00:42:19)
- The Reliability Function F (00:42:24)
- Reliability function for exponential failure distribution (00:42:24)
- 120 (00:42:24)
- Failure experience (00:42:24)
- Increasing probability of failure (00:42:24)
- Variable Failure Rate in Real World (00:44:18)
- Hardware Failure Rate (00:49:24)
- Software Failure Rate (00:49:43)
- Failure Rate Examples (00:50:27)
- Example Item Level 5 Sparing Analysis Sparing analysis challenges (00:53:53)
- Steady State Availability (00:54:27)
- Mean time between failures (00:54:27)
- Mean time to recover repair (00:54:27)
- Mean time to failure (00:54:27)
- Steady State Availability and Expressing reliability with imply a repairable system (00:57:54)
- Example (01:00:54)
- in Practice (01:07:35)
- Operational Availability Calculation (01:08:11)
- Examples (01:08:13)
- Steady State Availability (01:09:07)
- Examples (01:09:08)
- Steady State Availability (01:10:32)
- Fox (01:12:36)
- 1968 distracted moves (01:12:36)
- factor of failed system (01:12:36)
- Lowering directly improves user experience of one specific since (01:12:36)
- Armando Fox on Recovery Oriented Computing (01:12:36)
- they show a preference for increased latency vs worse vs being turned (01:12:54)
- For how long will users tolerate temporary degradation (01:12:54)
- If error state leads to some steady state latency (01:12:54)
- Key distinction between interactive and non interactive systems (01:12:54)
- Availability (01:14:10)
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