Luping Chen

Assessment of the Benefit of Redundant Systems

The evaluation of the gain in reliability of mult-iversion software is one of the key issues in the safety assessment of high integrity systems. Fault simulation has been proposed as a practical method to estimate diversity of multi-version software. This paper applies data-flow perturbation as an implementation of the fault injection technique to evaluate redundant systems under various conditions. A protection system is used as an example to illustrate the evaluation of software structural diversity, optimal selection of channel-pairs and the assessment of different designs.

A Constant Perturbation Method for Evaluation of Structural Diversity in Multiversion Software

In this paper, fault simulation is discussed as a test method for diversity assessment of multiversion software and data flow perturbation is used as a main technique for implementation. More specifically, constant perturbation is introduced as a specific example of data-flow perturbation. Some quantitative metrics are proposed for the description of software diversity, and the parameters needed to calculate the metrics estimated by fault injection experiments. A case study is presented to illustrate that the diversity metrics are appropriate, and that constant perturbation is a practical fault injecting technique to estimate parameters necessary for assessing diversity.

A Diversity Model Based on Failure Distribution and Its Application in Safety Cases

This work develops a new basis for evaluating the reliability benefits of diverse software, based on fault injection testing. In particular, the work investigates new forms of argumentation that could in principle be used to justify diversity as a basis for the construction of safety claims. Failure distributions of two versions of diverse software under various fault conditions are revealed separately by fault injection methods, and then the common failure probability of the version-pair can be estimated. The approach is justified theoretically, and cross validated with other work. This method is also used to explain the fundamental influence of failure distributions on diversity. Furthermore, the unique capabilities of the method are demonstrated by implementation of the fault injection test on a program pair.