Exponential order statistic models of software reliability growth
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
Optimal release time of improved versions of software packages
Information and Software Technology - Software quality assurance
Determining component reliability using a testing index
ACSC '02 Proceedings of the twenty-fifth Australasian conference on Computer science - Volume 4
Moral Hazard, ethical considerations, and the decision to implement an information system
Journal of Management Information Systems
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We develop a methodology to measure the quality levels of a number of releases of a software product in its evolution process. The proposed quality measurement plan is based on the faults detected in field operation of the software. We describe how fault discovery data can be analyzed and reported in a framework very similar to that of the QMP (quality measurement plan) proposed by B. Hoadley (1986). The proposed procedure is especially useful in situations where one has only very little data from the latest release. We present details of implementation of solutions to a class of models on the distribution of fault detection times. The conditions under which the families: exponential, Weibull, or Pareto distributions might be appropriate for fault detection times are discussed. In a variety of typical data sets that we investigated one of these families was found to provide a good fit for the data. The proposed methodology is illustrated with an example involving three releases of a software product, where the fault detection times are exponentially distributed. Another example for a situation where the exponential fit is not good enough is also considered.