Abstract
The hyper-geometric distribution model (HGDM) has been presented as a software reliability growth model with the capability to make estimations for various kinds of real observed test-and-debug data. With the HGDM, the discovery and rediscovery of faults during testing and debugging has been discussed. One of the parameters, the 'ease of test' function w(i) represents the total number of faults discovered and rediscovered at a test instance. In this paper, the authors firstly show that the ease of test function w(i) can be expressed as a function of the test coverage for the software under test. Test coverage represents a measure of how much of the software has been tested during a test run. Furthermore, the ease of test function w(i) can integrate a user-experience based parameter c that represents the strength of test cases to discover faults. This parameter c allows the integration of information on the goodness of test cases into the estimation process. The application of the HGDM to a set of real observed data clearly shows that the test coverage measure can be integrated directly into the ease of test function w(i) of the model. >
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