Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Rationale for fault exposure ratio K
ACM SIGSOFT Software Engineering Notes
Program structure and dynamic models of software reliability: investigation in a simulation environment
An Examination of Fault Exposure Ratio
IEEE Transactions on Software Engineering - Special issue on software reliability
Optimizing preventive service of software products
IBM Journal of Research and Development
What do the Software Reliability Growth Model Parameters Represent?
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
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One of the most important parameters that control reliability growth is the fault exposure ratio (FER) identified by J.D. Musa et al. (1991). It represents the average detectability of the faults in software. Other parameters that control reliability growth are software size and execution speed of the processor which are both easily evaluated. The fault exposure ratio thus presents a key challenge in our quest towards understanding the software testing process and characterizing it analytically. It has been suggested that the fault exposure ratio may depend on the program structure, however the structuredness as measured by decision density may average out and may not vary with program size. In addition FER should be independent of program size. The available data sets suggest that FER varies as testing progresses. This has been attributed partly to the non-randomness of testing. We relate defect density to FER and present a model that can be used to estimate FER. Implications of the model are discussed. This model has three applications. First, it offers the possibility of estimating parameters of reliability growth models even before testing begins. Secondly, it can assist in stabilizing projections during the early phases of testing when the failure intensity may have large short term swings. Finally, since it allows analytical characterization of the testing process, it can be used in expressions describing processes like software test coverage growth.