Impact of program transformation on software reliability assessment

The statistical sampling method is a theoretically sound approach for measuring the reliability of safety critical software, such as control systems for nuclear power plants, aircrafts, space vehicles, etc. It has, however some practical drawbacks, two of which are the large number of test cases needed to attain a reasonable confidence in the reliability estimate and the sensitivity of the reliability estimate to variations in the operational profile. One way of dealing with both of these issues is to combine statistical sampling with formal methods and attempt to verify complete program paths. This combination becomes especially effective if high usage paths are verified. However the verification of complete paths is difficult to perform in practice and viable only when there is a high confidence in the correctness of the specification. We identify program transformations and partial proofs which have a measurable impact on the reliability assessment procedure. These methods reduce the effective size of the input space which can facilitate sampling without replacement, thereby increasing the confidence in the reliability estimate. Furthermore, these techniques increase the probability that the program under test is free of errors if testing reveals no failures.