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Estimating Worst Case Failure Dependency with Partial Knowledge of the Difficulty Function

Bishop, P. G. & Strigini, L. (2014). Estimating Worst Case Failure Dependency with Partial Knowledge of the Difficulty Function. Paper presented at the 33rd International Conference, SAFECOMP 2014, 10-09-2014 - 12-09-2014, Florence, Italy. doi: 10.1007/978-3-319-10506-1


For systems using software diversity, well-established theories show that the expected probability of failure on demand (pfd) for two diverse program versions failing together will generally differ from what it would be if they failed independently. This is explained in terms of a “difficulty function” that varies between demands on the system. This theory gives insight, but no specific prediction unless we have some means to quantify the difficulty func-tion. This paper presents a theory leading to a worst case measure of “average failure dependency” between diverse software, given only partial knowledge of the difficulty function. It also discusses the possibility of estimating the model parameters, with one approach based on an empirical analysis of previous sys-tems implemented as logic networks, to support pre-development estimates of expected gain from diversity. The approach is illustrated using a realistic safety system example.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: The final publication is available at Springer via
Publisher Keywords: safety, software reliability, fault tolerance, failure dependency, software diversity, difficulty function
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Science & Technology > Computer Science > Software Reliability
Text - Accepted Version
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