Comparing Software Prediction Techniques Using Simulation
IEEE Transactions on Software Engineering - Special section on the seventh international software metrics symposium
Table Oriented Metrics for Relational Databases
Software Quality Control
Measuring for Database Programs Maintainability
DEXA '00 Proceedings of the 11th International Conference on Database and Expert Systems Applications
Complexity measures in 4GL environment
ICCSA'11 Proceedings of the 2011 international conference on Computational science and Its applications - Volume Part V
A correlational study on four measures of requirements volatility
EASE'08 Proceedings of the 12th international conference on Evaluation and Assessment in Software Engineering
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An important task for any software project manager is to be able to predict and control project size and development effort. Unfortunately, there is comparatively little work, other than function points, that tackles the problem of building prediction systems for software that is dominated by data considerations, in particular systems developed using 4GLs. We describe an empirical investigation of 70 such systems. Various easily obtainable counts were extracted from data models (e.g. number of entities) and from specifications (e.g. number of screens). Using simple regression analysis, a prediction system of implementation size with accuracy of MMRE = 21% was constructed. This approach offers several advantages. First, there tend to be fewer counting problems than with function points since the metrics we used were based upon simple counts. Second, the prediction systems were calibrated to specific local environments rather than being based upon industry weights. We believe this enhanced their accuracy. Our work shows that it is possible to develop simple and useful local prediction systems based upon metrics easily derived from functional specifications and data models, without recourse to overly complex metrics or analysis techniques. We conclude that this type of use of metrics can provide valuable support for the management and control of 4GL and database projects.