Several methods have been explored for assuring the reliability of mission critical systems (MCS), but no single method has proved to be completely effective. This paper presents an approach for quantifying the confidence in the probability that a program is free of specific classes of defects. The method uses memory-based reasoning techniques to admit a variety of data from a variety of projects for the purpose of assessing new systems. Once a sufficient amount of information has been collected, the statistical results can be applied to programs that are not in the analysis set to predict their reliabilities and guide the testing process. The approach is applied to the analysis of Y2K defects based on defect data generated using fault-injection simulation.
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