Empirical Modeling:
Optimized Set Reduction
Approach
Validation Strategy
Different modeling approaches have been compared and evaluated based on data from the Software Engineering Laboratory (SEL).
Project Status
Results
Modeling
Algorithms to generate patterns and merge similar patterns according
to a user defined degree of similarity have been designed.
A prototype has been built, and a commercial tool has been developed by
a software company in France.
Validation
First, we demonstrated the effectiveness of the approach by applying
OSR to the problem of cost estimation. The OSR predictions were compared
to predictions from two other effort estimation techniques to provide a
basis for evaluation. The data set for the study came from the COCOMO database
and the fifteen projects used by kemere for cost modeling evaluation.
Then, we validated the approach by applying OSR constructing a predictive
effort model for changes during the maintenance phase. We used a data set
describing several projects in the SEL at the NASA Goddard Space Flight
Center (GSFC).
We also validated the OSR appraoch by comparing it to standard modeling
approaches currently used for classification such as logistic regression
and classification trees. The approaches were applied to early identify
the high-risk system components. The data set included 146 components of
a 260 KLOC Ada system from the NASA/GSFC Flight Dynamics Division.
