This research develops a set of predictive measures enabling software
testers and designers to identify and target potential problem areas for additional
and/or enhanced testing. Predictions are available as early in the design process
as requirements allocation and as late as code walk-throughs. These predictions
are based on characteristics of the design artifacts prior to coding.
Prediction equations are formed at established points in the software
development process called milestones. Four areas of predictive measurement
are examined at each design milestone for candidate predictive metrics. These
areas are: internal corrlplexity, information flow, defect categorization, and the
change in design. Prediction equations are created from the set of candidate
predictive metrics at each milestone. The most promising of the prediction
equations are selected and evaluated. The single "best" prediction equation is
selected at each design milestone.
The resulting predictions are promising in terms of ranking areas of the
software design by the number of predicted defects. Predictions of the actual
number of defects are less accurate.
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