Abstract
Software reliability is the probability of failure-free operations of software in a specific environment in a given time period. Various software reliability models have been designed by the researchers, but the JM model is the first influential model. The JM model was developed with the basic assumption that the faults are independent in this model and the debugging process is perfect. But practically, all debugging processes may not be perfect, especially when the faults are dependent; in this case, the fault that is actually to have been removed may also remove more than one fault and cause it to add some new faults. To handle this behavior of faults mutual dependency, we need a new model which may be less reliable or the result accuracy of the model may be lower than that of the existing ones, but it can handle more practical situations in the fault removal process. In this paper, we proposed a new software reliability model with the same assumption that at whatever time a failure is detected, it is not completely eradicated and there is a possibility of raising some new faults because of wrong analysis or inaccurate modifications in the software or the removal of the existing fault may also remove some other faults. The proposed model is more practical than the existing ones.
Highlights
Software reliability models are used to find the faults in a software product, and for the prediction of faults, these models predict and estimate the number of faults in the build
We have extended the JM model by replacing these assumptions with the new assumptions that the faults are dependent and not likely to cause a failure in the test, and whenever a failure occurred, the identified faults are removed with probability p, and it may result in the removal and generation of some other faults, from the total number of faults, with random probabilities r, such that p > r, respectively
Model Assumptions. e assumptions considered in the JM model are given as follows: (i) ere are unknown numbers of faults in the software initially and these fault counts are fixed and constant (ii) e faults are not dependent on each other and likely to cause a failure during a test (iii) ere are independent time intervals among the occurrences of failures, exponentially distributed random variables (iv) e software failure rate remains constant over the intervals between fault occurrences (v) e failure rate is directly proportional to the number of faults that linger in the software (vi) A detected fault is eliminated immediately, and no new faults are initiated during the elimination of the detected fault (vii) When a failure occurs, the corresponding fault is removed with certainty
Summary
Kuldeep Singh Kaswan, Sunita Choudhary, Santar Pal Singh ,3 Anil Audumbar Pise ,4 and Simon Karanja Hinga 5. All debugging processes may not be perfect, especially when the faults are dependent; in this case, the fault that is to have been removed may remove more than one fault and cause it to add some new faults. To handle this behavior of faults mutual dependency, we need a new model which may be less reliable or the result accuracy of the model may be lower than that of the existing ones, but it can handle more practical situations in the fault removal process. We proposed a new software reliability model with the same assumption that at whatever time a failure is detected, it is not completely eradicated and there is a possibility of raising some new faults because of wrong analysis or inaccurate modifications in the software or the removal of the existing fault may remove some other faults. e proposed model is more practical than the existing ones
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