Over the past 40 years limited progress has been made to help practitioners estimate the risk and the required effort necessary to deliver software solutions. Recent developments improve this outlook, one in particular, the research of Juan Carlos Nogueira. Dr. Nogueira developed a formal model for risk assessment that can be used to estimate a software projectαs risk when examined against a desired development time-line. Dr. Nogueira developed his model based on data collected from a series of experiments conducted on the ViteÌ Project simulation. This unique approach provides a starting point towards a proven formal model for risk assessment. Another issue with software development, especially in the Department of Defense (DoD), is dealing with aging legacy software systems. These systems perform the functionality of their design, but their interfaces are obsolete and changing requirements limit their functional usefulness. This thesis is an exercise in upgrading a legacy system licensed to the DoD, ViteÌ Project, for use with ongoing DoD research that seeks to discern truly quantifiable criteria that can be used to more accurately estimate the length of time needed to complete any software project. Accurately projecting software development times and accurate software development costs have eluded software developers for decades. / US Navy (USN) author

Thesis (M.S in Computer Science) Naval Postgtaduate School, December 2001. / Thesis Advisor(s): Berzins, Valdis ; Murrah, Michael. "December 2001." Includes bibliographical references (p. 91). Also available online.

Thesis (Ph.D.)--University of Texas at Dallas, 2008. / Includes vita. Includes bibliographical references (leaves 138-145)

The main goal of this work is to analyze existing popular software size estimation and project completeness schedule methods and models, find advantages and disadvantages, try to combine them for using together, searching for common properties. The combination of these methods and models will give a new model, which will be tested with experimental research.

[Truncated abstract] The primary tool for software process control is the project plan, with divergence from the schedule usually being the first indication that there are difficulties. Thus the estimation of the schedule, particularly the effort parameter, is a central element of software engineering management. Regrettably, estimation methods are poorly used within the software industry and accuracy is lacking when compared with other engineering disciplines. There are many reasons for this. However, the need to predict project effort remains, particularly in situations of tendering for contracts. The broad objective of this research is the improvement of project control by means of better estimation. . . The error in the prediction of a project parameter is investigated as the result of the variation in two distinct (estimation and actual development) processes. Improvement depends upon the understanding, control and then reduction of that variation. A strategy for the systematic identification of the sources of greatest variation is developed - so that it may be reduced by appropriate software engineering practices. The key to the success of the approach is the statistical partitioning of the Mean Square Error (of the estimate) in order to identify the weakest area of project control. The concept is proven with a set of student projects, where the estimation error is significantly reduced. The conditions for its transfer to industry are discussed and a systematic reduction in error is demonstrated on five sets of commercial project data. The thesis concludes with a discussion of the linking of the approach to current estimation methods. It should also have implications for the statistical process control of other projects involving small sample sizes and multiple correlated parameters.

<p>Due to changes in the economy, the Department of Defense is requiring dramatic changes in its procurement process for major systems. These changes attempt to leverage from the large quantity of commercial software that is currently on the. market. As a result, better estimating techniques are required to properly account for software reuse. For government agencies, these techniques must be understood and applied when validating and tracking contractor performance. An industry survey was performed and subsequently two techniques were evaluated. The evaluation criteria used is consistent with the attributes of the systems engineering process. This project will evaluate the two most widely used; function point analysis and rule of thumb analysis were selected for computing the cost of a specified software intensive project.</p> / Master of Science

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