Reducing Safety-Critical Software Statistical Testing Cost Based on Importance Sampling Technique

Safety-critical software often includes some rarely executed critical operations that are often inadequately tested in statistical testing based reliability estimation. However, it is necessary to assess the reliability of safety-critical software to a high degree of confidence before it is deployed in the field. This paper discusses how to reduce safety-critical software statistical testing cost based on importance sampling technique. When both the critical operations and the entire software are adequately tested, the method can still compute the unbiased software reliability from the test results with much less test cases. Thus, the statistical testing cost of safety-critical software can be reduced effectively The simulated annealing algorithm for calculating optimum transition probabilities of the Markov chain usage model for reducing software statistical testing cost is also presented.