Evan P. Amato

Date of Award

3-2021

Document Type

Thesis

Degree Name

Master of Science in Cost Analysis

Department

Department of Systems Engineering and Management

First Advisor

Scott T. Drylie, PhD

Abstract

The productivity of software developers has been an area of interest in the private industry in an endeavor to more appropriately interpret pertinent software development cost drivers. In an effort to better predict the cost of developing software, many have focused on Application Type as an important factor. The Department of Defense (DoD) has recently adopted a similar focus. Studies on categorization schemes of Application Types have shown increasingly relevant cost and productivity driving characteristics recently in the DoD. Identification of factors associated with distinct productivity effects is important for the defense acquisition and software cost estimation domains. Distinct factors can provide insight into what drives software productivity and cost. This research attempts to investigate the significance of Application Type and Super Domain in predicting productivity in software intensive defense programs. This current study analyzed 655 Software Resource Data Reports of DoD projects spanning the years 2001 to 2019. The analysis indicates the significance of Application Type in predicting productivity to be overstated for DoD. Only two of seventeen Application Types adopted by the DoD and one of four larger environmental settings called “Super Domains” proved significant. Regarding those, this study was able to identify characteristics that may prove more useful for understanding drivers of software cost and productivity.

AFIT Designator

AFIT-ENV-MS-21-M-202

DTIC Accession Number

AD1133745

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