To mitigate the risk of some event causing damage, you must first estimate the probability that the event will occur. This probability has to be translated into some quantity, usually represented as a percentage-for example, "There is a 50 percent chance that this will happen." Next, you need to determine the severity of such a failure. Severity is usually measured in currency, such as dollars, and loss of life. If the severity is minor, then even a high probability of occurrence may still be judged to cause a trivial problem.
The probability that a thing will or won't occur can be calculated under certain circumstances-especially if you can answer a question like, "What was the outcome last time?" or "Do we know if the platform can really do what the maker claims it can?" If you can't provide a good measured answer to these questions up front, then you will need a strategy for dealing with the events that will occur later in the process. If the probability and severity cannot be measured, then they must be estimated. MITs risk analysis provides a formal method for both estimating up front and dealing with events as they unfold. In this chapter, we look at this formal approach to establishing risk and prioritizing the items on the test inventory.
MITs risk analysis uses both quantitative and qualitative analysis to establish a numeric value for risk based on a number of specific criteria. In the early planning phases of a test effort, this risk number is used to focus test resources to size the test effort. As the inventory evolves, the risk ranking plays an important part in actual test selection and optimal test coverage determination.
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