Graduation Semester and Year




Document Type


Degree Name

Master of Science in Computer Science


Computer Science and Engineering

First Advisor

David Levine


The goal of this study is to explore an effective way to provide timely and accurate size estimates for software and for an enterprise data warehouse (EDW). Several research papers attempt to adapt function point (FP) analysis to EDW, but there is not much research in comprehensive techniques to estimate large EDW projects. Despite the generality of FP, it is challenging to employ in an EDW environment. This thesis describes such a technique. Additionally, the thesis provides an overview of general estimating approaches, techniques, models, and tools.This work presents a software tool that is a custom built estimation utility that takes into account nuances of an EDW. Some of these nuances include type of technology being built; build object complexity, data complexity, and source to target mappings. The utility then uses these components to estimate project effort, and at the same time, provides a common mechanism to communicate such mission-critical estimates to planning teams, delivery teams, managers, and software architects. To evaluate the effectiveness of this tool, this work then shifts to a quantitative analysis section that compares the estimated numbers from multiple large-scale projects, with data from actuals. Specifically, the analysis examines estimates produced by expert judgment techniques and then compares these estimates to ones produced by the estimation utility. Following that, the differences between the two data sets provide a foundation for some statistical analysis and some comparisons of numerous behavioral drivers. Finally, evaluating the three large commercial EDW projects at a national airline, the tool predicted the actual project level of effort within ten to twenty percent accuracy.


Computer Sciences | Physical Sciences and Mathematics


Degree granted by The University of Texas at Arlington