Measures of testability as a basis for quality assurance
Software Engineering Journal
A Theory of Fault-Based Testing
IEEE Transactions on Software Engineering
Testability of Software Components
IEEE Transactions on Software Engineering
PIE: A Dynamic Failure-Based Technique
IEEE Transactions on Software Engineering
Faults on its sleeve: amplifying software reliability testing
ISSTA '93 Proceedings of the 1993 ACM SIGSOFT international symposium on Software testing and analysis
Dynamic impact analysis: a cost-effective technique to enforce error-propagation
ISSTA '93 Proceedings of the 1993 ACM SIGSOFT international symposium on Software testing and analysis
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
A semantic model of program faults
ISSTA '96 Proceedings of the 1996 ACM SIGSOFT international symposium on Software testing and analysis
On the Use of Testability Measures for Dependability Assessment
IEEE Transactions on Software Engineering
Software Assessment: Reliability, Safety, Testability
Software Assessment: Reliability, Safety, Testability
Predicting Where Faults Can Hide from Testing
IEEE Software
Software Testability: The New Verification
IEEE Software
Quantitative evaluation of software quality
ICSE '76 Proceedings of the 2nd international conference on Software engineering
Test Case Prioritization: An Empirical Study
ICSM '99 Proceedings of the IEEE International Conference on Software Maintenance
Measuring the strength of information flows in programs
ACM Transactions on Software Engineering and Methodology (TOSEM)
An empirical study on the usage of testability information to fault localization in software
Proceedings of the 2011 ACM Symposium on Applied Computing
Squeeziness: An information theoretic measure for avoiding fault masking
Information Processing Letters
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A number of different concepts have been proposed that, loosely speaking, revolve around the notion of software testability. Indeed, the concept of testability itself has been interpreted in a variety of ways by the software community. One interpretation is concerned with the extent of the modifications a program component requires, in terms of its input and output variables, so that the entire behaviour of the component is observable and controllable. Another interpretation is the ease with which faults, if present in a program, can be revealed by the testing process and the propagation, infection and execution (PIE) model has been proposed as a method of estimating this. It has been suggested that this particular interpretation of testability might be linked with the metric domain-to-range ratio (DRR), i.e. the ratio of the cardinality of the set of all inputs (the domain) to the cardinality of the set of all outputs (the range). This paper reports work in progress exploring some of the connections between the concepts mentioned. In particular, a simple mathematical link is established between domain-to-range ratio and the observability and controllability aspects of testability. In addition, the PIE model is re-considered and a relationship with fault size is observed. This leads to the suggestion that it might be more straightforward to estimate PIE testability by an adaptation of traditional mutation analysis. The latter suggestion exemplifies the main goals of the work described here, namely to seek greater understanding of testability in general and, ultimately, to find easier ways of determining it.