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Q. Explain Predictive validity?
Predictive validity: It is the potential of the model to predict future failure behaviour from present and past failure behaviour. This capability is important only when failure behaviour is changing. There are two universal ways of viewing predictive validity based on the two equivalent approaches to characterizing failure random process namely
1. The number of failure approach as well as
2. The failure time approach.
We can visually ensure the predictive validity by plotting the relative error against the normalised test time.
What is ripple effect? The ripple effect is a term used to describe a situation where, like the ever expanding ripples across water when an object is dropped into it, an
Q. Illustrate Partitioning in stepwise refinement? Problems are frequently too large and complex to be understood as a whole. Therefore we tend to partition such problems into
How do we zero down on automation tools for regression testing? Below criteria are used when zeroing down on automation tools for regression testing: - Risk analysis such as
What is equivalence partitioning? Equivalence partitioning is a black box procedure that divides the input domain into classes of data. From this data test cases can be foun
Two partners in an upholstery business are interested in decreasing the number of complaints from customers who have had furniture reupholstered by their staff. For the past six mo
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Explain Software Bug? Ans) A fault in a program which origins the program to perform in an unintended or unanticipated manner.
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Define Requirement Engineering . Requirement Engineering is a process in which all of the activities required to maintain and create a system requirements document. The four
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