A replicated empirical study of a selection method for software reliability growth models

  • Andersson C
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Replications are commonly considered to be important contributions to investigate the generality of empirical studies. By replicating an original study it may be shown that the results are either valid or invalid in another context, outside the specific environment in which the original study was launched. The results of the replicated study show how much confidence we could possibly have in the original study. We present a replication of a method for selecting software reliability growth models to decide whether to stop testing and release software. We applied the selection method in an empirical study, conducted in a different development environment than the original study. The results of the replication study show that with the changed values of stability and curve fit, the selection method works well on the empirical system test data available, i.e., the method was applicable in an environment that was different from the original one. The application of the SRGMs to failures during functional testing resulted in predictions with low relative error, thus providing a useful approach in giving good estimates of the total number of failures to expect during functional testing. � Springer Science+Business Media, LLC 2007.

Author-supplied keywords

  • Computer system recovery
  • Data reduction
  • Empirical systems
  • Functional testing
  • Mathematical models
  • Parameter estimation
  • Replication
  • Software reliability
  • Software reliability growth models
  • System stability

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  • C Andersson

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