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Q. Explain Basic Execution Time Model?
The model was developed by the J.D. MUSA in 1979(MUSA79) and is based on execution time. It is presumed that failures may occur according to a non-homogeneous Poisson Process (NHPP) Real world events may be described using Poisson processes. Instance of Poisson processes are
- A Number of telephone calls expected in a given period of time
- Expected figure of road accidents in a given period of time
- Expected figure of persons visiting in a shopping mall in a given period of time.
In this model the reduce in failure intensity as a function of the number of failures observed is constant and is given as:
Where Initial failure intensity at the start of execution.
V0 Number of failures experienced, if program is executed for Infinite time period μ Average as well expected number of failures experienced at a given point in time. These models imply a uniform operational profile. If every input class are selected equally often the various faults have an equal probability of manifesting themselves. The correction of whichever of those faults then contributes an equal decrease in the failure intensity. The negative sign publicized that there is a negative slope meaning thereby a decrementing trend in failure intensity.
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Q. Explain Basic Execution Time Model? The model was developed by the J.D. MUSA in 1979(MUSA79) and is based on execution time. It is presumed that failures may occur according
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