A comparison of effort estimation methods for 4GL programs:
experiences with Statistics and Data Mining
José C. Riquelme, Macario Polo, Jesús S. Aguilar, Mario
Piattini, Francisco J. Ferrer, Francisco Ruiz
Abstract
This paper presents an empirical study analysing the relationship
between a set of metrics for Fourth{Generation Languages (4GL) programs
and their
maintainability. An analysis has been made using historical data of
several industrial
projects and three different approaches: the first one relates metrics
and
maintainability based on techniques of descriptive statistics, and the
other two are based on Data Mining
techniques. A discussion on the results obtained with the three
techniques is also
presented, as well as a set of equations and rules for predicting the
maintenance e®ort in
this kind of programs.
Finally, we have done experiments about the prediction accuracy of
these methods by using new unseen data, which were not used to build
the knowledge
model. The results were satisfactory as the application of each
technique separately
provides useful perspective for the manager in order to get a
complementary insight
from data.
International Journal of
Software Engineering and Knowledge Engineering, 16(1), 127-140.