## Basic Execution Time ModelThis model was established by J.D. Musa in 1979, and it is based on execution time. The basic execution model is the most popular and generally used reliability growth model, mainly because: - It is practical, simple, and easy to understand.
- Its parameters clearly relate to the physical world.
- It can be used for accurate reliability prediction.
The basic execution model determines failure behavior initially using execution time. Execution time may later be converted in calendar time. The failure behavior is a process whose characteristics vary in time. It is equivalent to the The mean value function, in this case, is based on an exponential distribution.
In the basic execution model, the mean failures experienced μ is expressed in terms of the execution time (τ) as
The failure intensity expressed as a function of the execution time is given by It is based on the above formula. The failure intensity λ is expressed in terms of μ as:
For a derivation of this relationship, equation 1 can be written as: The above equation can be solved for λ(τ) and result in: The failure intensity as a function of execution time is shown in fig: Based on the above expressions, given some failure intensity objective, one can compute the expected number of failures ∆λ and the additional execution time ∆τ required to reach that objective.
This can be derived in mathematical form:
- Find the decrement of failure intensity per failure.
- Calculate the failures experienced and failure intensity after 20 and 100 CPU hrs. of execution.
- Compute addition failures and additional execution time required to reach the failure intensity objective of 5 failures/CPU hr.
Use the basic execution time model for the above-mentioned calculations.
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