A methodology for cost-effective software fault tolerance for mission-critical systems

As computing capabilities continue to advance, there will be a concurrent rise in the number of both hardware and software faults. These will be caused by the greater volume of more complex software, by the increased number of untested software states, and by more incidents of hardware/software interaction faults as a result of increased hardware speed and density. The traditional software implemented fault tolerance approaches have been successfully utilized in life-critical systems, such as digital flight controls, where their additional costs can be easily justified. Examples include N-Version Programming and Recovery Block approaches. However, there is still a need for dependable computing for mission-critical applications as well. Often, these traditional techniques are avoided for mission-critical systems due to the difficulty in justifying their extra upfront development cost. We provide an alternative for the high "sunk cost" of traditional software fault tolerance techniques. The methodology, called Data Fusion Integrity Processes (DFIPs), is a simple, yet effective technique for mission critical systems. In addition, the approach establishes a framework from which other costlier, more extensive traditional techniques can be added. We present details of the DFIP methodology and a DFIP framework for Ada programs. We also briefly discuss development of a DFIP code generation system which exploits Java that will enable users to quickly build a DFIP framework in Ada, and select reusable DFIP component methods.