No abstract

Our goal is to identify software m o dules that have some locations which do not propagate errors induced by a suite of test cases. This paper focuses on whether or not data state errors can propagate from a location in the code to the outputs or observable data state during random testing with inputs drawn from an operational distribution. If a c ode-location's probability of propagation is estimated t o b e zero, then a fault in that location could escape detection during testing. Because testing is never exhaustive, there is a risk that failures due to such latent faults could occur during operations.Fault injection is a technique for directly measuring the probability of propagation. However, measurement for every location in the code of a full-scale program is often prohibitively computation-intensive. Our objective is a practical, useful alternative to direct measurement.We present empirical evidence that static software p r oduct metrics can be useful for identifying software m o dules where the e ects of a fault in that module are not observable. A case study of an intricate computer game program revealed a useful empirical relationship between static software p r oduct metrics and propagation of errors. The case study program was an order of magnitude larger than previously reported studies.Readers may contact the authors through Taghi