Abstract
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, prediction systems of implementation size with accuracy of MMRE=21% were constructed. Our work shows that it is possible to develop simple and effective prediction systems based upon metrics easily derived from functional specifications and data models.