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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.
Define the factors of prime concern for system modeling Following four factors are of prime concern for system modeling: 1. System modeling is undertaken with some simplifyi
Explain the working of Gantt charts - Gantt charts enable emailing of project/tasks info to others automatically - Gantt charts allow use of intranet/email facility to down
how to create initialzer
What is COCOMO model? COCOMO stands for COnstructive COst MOdel. It is used for cost Effort=a * KDLOCb Where a and b are two parameters of the model whose specific values
java/python based application which lets you upload images of car logos and detects which logo it is by outputting the ID number of that image. Neural network is used to achieve th
A testing technique using input values at, just below, and just above, the definite limits of an input domain; and with input values causing outputs to be at, just below, and just
Q. Explain the relationship between Productivity and difficulty? Productivity refers to metrics as well as measures of output from production processes per unit of input. Pr
Q. Define cohesion and coupling? Give suitable examples. Ans Coupling: Coupling refers to the strength of the relationship between modules in a system. Coupling represents how
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Difference between Verification and Validation Verification is Static whereas Validation is Dynamic. This means in Verification the s/w is inspected by looking into the code go
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