Practitioners have expressed concern over their inability to accurately estimate costs associated with software development. This concern has become even more pressing as costs associated with development continue to increase. As a result, considerable research attention is now directed at gaining a better understanding of the software-development process as well as constructing and evaluating software cost estimating tools. This paper evaluates four of the most popular algorithmic models used to estimate software costs [SLIM, COCOMO, Function Points, and ESTIMACS). Data on 15 large completed business dataprocessing projects were collected and used to test the accuracy of the models' ex post effort estimation. One important result was that Albrecht's Function Points effort estimation model was validated by the independent data provided in this study [3]. The models not developed in business data-processing environments showed significant need for calibration. As models of the software-development process, all of the models tested failed to sufficiently reflect the underlying factors affecting productivity. Further research will be required to develop understanding in this area.
Kemerer's work REF is one of the first to report on the quantitative evaluation of early parametric estimation models, namely SLIM, COCOMO 81, Function Points and ESTIMACS.
An empirical validation of software cost estimation models
CACM
Computer Science