Date of Award


Document Type


Degree Name

Master of Science in Cost Analysis

First Advisor

Daniel V. Ferens, PhD


As more Department of Defense resources are being allocated toward software development, the necessity to accurately plan for software costs has become critical. Obtaining reliable estimates from software cost models, like PRICE S, can be a problem when input parameters are not precisely defined or calibrated. This research effort centered on refining Productivity Factor (PROFAC) values for defense industry applications. The Space and Missile Systems Center Database was used to calibrate PROFAC values for eleven stratified data sets: military ground, military mobile, missile, unmanned space, Ada, Assembly, C, COBOL, FORTRAN, JOVIAL, and PASCAL. The accuracy of the calibrations was determined through comparisons of calibrated and default generated estimates versus actuals. Statistical methods used to make the comparisons included standard deviation, mean absolute error, mean relative error, and percentage of records estimated within twenty-five percent of actuals. The results were surprising in that, in most instances, the calibrated PROFAC values estimated actual cost well, but not overwhelmingly better than the default PROFAC values. The main contributing factor to this phenomena was variability within the stratified data sets. The results were encouraging, however, in that the results from seven of the eleven stratified data sets suggested either a new refinement in PROFAC values based upon the calibration or the recommendation to use PROFAC values from analogous calibrated records for estimating future efforts.

AFIT Designator


DTIC Accession Number



The author's Vita page is omitted.

Presented to the Faculty of the Graduate School of Logistics and Acquisition Management of the Air Force Institute of Technology.