Safety verification in Murphy using fault tree analysis
ICSE '88 Proceedings of the 10th international conference on Software engineering
Testability of Software Components
IEEE Transactions on Software Engineering
Semantic metrics for software testability
Journal of Systems and Software - Special issue on the Oregon Metric Workshop
An Analysis of Test Data Selection Criteria Using the RELAY Model of Fault Detection
IEEE Transactions on Software Engineering
On the Use of Testability Measures for Dependability Assessment
IEEE Transactions on Software Engineering
Some Conservative Stopping Rules for the Operational Testing of Safety-Critical Software
IEEE Transactions on Software Engineering
Software Testability: The New Verification
IEEE Software
A new approach for software testability analysis
Proceedings of the 28th international conference on Software engineering
| Hi-index | 0.00 |
One of the definitions for testability is the probability whether tests will detect a fault, given that a fault in the program exists. The testability can be estimated from the probability of each statement fault leading to output failure. The probability of the test detecting a fault depends on the probability of individual statement faults appearing as an output failure when a fault exists at a statement. The testability measure of the software has been introduced based on output failure probability and the entropy of the impartance of basic statements to the output failure from the software fault tree analysis. The output failure probability and the impartance of statements are calculated from software fault tree analysis. The suggested testability measure has been applied to the two modules of the safety system in a nuclear power plant. The proposed testability measure can be used for the selection of output variables or to determine the modules that are more vulnerable to undetected faults.