Interaction fault tolerance

Warning patterns Consider the example of a tank used for some chemical processing, with sensors for temperature, pressure and PH. The result of hazard analysis may indicate that leakage from one of the valves should raise the temperature and pressure and lower the PH. If the save valve is stuck closed, the temperature should raise and the pressure and PH should get lower values. Similar data, with different results, may be obtained about other valves. If the tank leaks, the temperature and pressure may decrease and the PH would remain unchanged. What we get is a map of trends in sensor data due to hazards. We can use this map at run time to direct the operator to the source of warning messages.
Sensor reliability What if one of the sensors get stuck? In safety-critical systems the system should trace the changes in the sensors and notify on sensors that always give the same values.
Repeating exceptional states When an exceptional state repeats, the feedback message becomes annoying. Developers are often tempted to replace the feedback message by beeps, which are less annoying, or to just ignore the event. This kind of response is risky, because the operator might not know the reason for ignoring the action, and might not know that the system is in an exceptional state. A safer approach is identify the annoying exceptional states and include them as new scenarios in the state model, and then to specify the system response according to the operators’ tasks.