Classes of Cost Estimation Models 1 Running Head: CLASSES OF COST ESTIMATION MODELS MetaTech Consulting, Inc. White Paper Classes of Software Cost Estimation Models with Consideration to Influential Factors

This paper presents a discussion of two classes of software cost estimation models: parametric and heuristic. A brief treatment of each class is followed by a summarization of some of the more prevalent models within the respective class. The parametric class of models is demonstrated through a discussion of the most current version of the Constructive Cost Model (COCOMO 2.0) model and the Function Point Analysis model. An elementary representation of the formulas used for each model is provided to illustrate the most influential factors of each. The bottom-up, top-down, and estimation by analogy models are offered as examples of heuristic cost estimation models. The conclusion summarizes the classes of cost estimation models and illuminates the strengths and weakness of each. Classes of Cost Estimation Models 3 Classes of Software Cost Estimation Models with Consideration to Influential Factors Effective project management necessitates accurate estimations of time, material, and resources. Estimates are generally needed very early in the development lifecycle though their accuracy is least in the beginning phases. Agarwal et al. (2001) assert that software cost estimation is a continual process present throughout a project lifecycle (Figure 1). By comparing estimates with actual metrics, it is possible to improve the process with each iteration. For nearly fourth years researchers and practitioners have endeavored to synthesize and improve models to produce more accurate and reliable cost estimations for software intensive systems. The present essay draws on some of the most recent research in the field to help illuminate the reader on the maturation of the models being used and the factors that contribute to their accuracy. The purpose of this paper is to convey to the reader in a concise form an understanding of cost estimation models, how and when they are best used, and the factors that practitioners must be aware of to better select from the alternatives.