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New Ways to Get Accurate Reliability Measures
July/August 1992 (vol. 9 no. 4)
pp. 34-42

Two techniques that analyze prediction accuracy and enhance predictive power of a software reliability model are presented. The u-plot technique detects systematic differences between predicted and observed failure behavior, allowing the recalibration of a software reliability model to obtain more accurate predictions. The perpetual likelihood ratio (PLR) technique compares two models' abilities to predict a particular data source so that the one that has been most accurate over a sequence of predictions can be selected. The application of these techniques is illustrated using three sets of real failure data.

Index Terms:
reliability measures; prediction accuracy; predictive power; software reliability model; u-plot technique; recalibration; perpetual likelihood ratio; data source; real failure data; software reliability
Citation:
Sarah Brocklehurst, Bev Littlewood, "New Ways to Get Accurate Reliability Measures," IEEE Software, vol. 9, no. 4, pp. 34-42, July-Aug. 1992, doi:10.1109/52.143100
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