Issue No. 04 - July/August (1992 vol. 9)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/52.143100
<p>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.</p>
reliability measures; prediction accuracy; predictive power; software reliability model; u-plot technique; recalibration; perpetual likelihood ratio; data source; real failure data; software reliability
B. Littlewood and S. Brocklehurst, "New Ways to Get Accurate Reliability Measures," in IEEE Software, vol. 9, no. , pp. 34-42, 1992.