This document discusses patterns for fault detection in software systems. It describes a priori detection using constraints on system states, results and side effects. It also covers comparing redundant results to identify faulty components, and using techniques like Bayesian learning to determine correct system behavior. Finally, it distinguishes between detecting errors, failures, and faults, noting that errors should be detected and corrected before resulting in failures through techniques like fail-silent crash detection and try/catch blocks.

1. Pattern for Fault
Tolerant Software
Chapter 5. Detection Patterns

2. The first phase of fault
tolerance is detection

3. The dimensions of detection

4. A Priori Detection
use constraints
System states, Result, Side effects
If nothing is known about the range of
results this method will obviously not work.

5. Comparing Redundant
Results
Redundancy ( 3 , chapter 4)
The value to be compared or
The context to enable the identification of
the faulty component

6. To learn about correct system behavior
ex) Bayesian learning technique

7. Just determining that
one is incorrect is helpful,
but insufficient to fix the fault and
prevent a failure from occurring

8. Detect an Error >Detect a failure

9. The error is detected
automatically and corrected
before it becomes a failure
‘fail-silent’ and crash failure mode
element stops without informing them that it is stopping
detecting that an element has stopped functioning
vs
determining if an element has stopped operating correctly

10. Test function return codes
try/catch
Detecting Errors

13. Next - Fault Correlation