Enhancing input value selection in parametric software cost estimation models through second level cost drivers

Parametric cost estimation models are widely used effort prediction tools for software development projects. These models are based on mathematical models that use as inputs specific values for relevant cost drivers. The selection of these inputs is, in many cases, driven by public prescriptive rules that determine the selection of the values. Nonetheless, such selection may in some cases be restrictive and somewhat contradictory with empirical evidence, in other cases the selection procedure is somewhat subject to ambiguity. This paper presents an approach to improve the quality of the selection of adequate cost driver values in parametric models through a process of adjustment to bodies of empirical evidence. The approach has two essential elements. Firstly, it proceeds by analyzing the diverse factors potentially affecting the values a cost driver input might adopt for a given project. And secondly, an aggregation mechanism device for the selection of input variables based on existing data is explicitly devised. This paper describes the rationale for the overall approach and provides evidence of its appropriateness through a concrete empirical study that analyses the COCOMO II DOCU cost driver.Sin financiación0.438 SJR (2006) Q1, 15/95 Media technology; Q3, 186/459 SoftwareUE

Cost estimation and management over the life cycle of metallurgical research projects

This study investigates whether all expected costs over the life cycle of metallurgical research projects are included in initial, normal and final cost estimates, and whether these costs are managed throughout a project’s life cycle since there is not enough emphasis on the accurate estimation of costs and their management over the life cycle of metallurgical research projects. The study also determines during which phase of the life cycle of metallurgical research projects’ costs are normally determined, during which phase most of the costs are incurred, and during which phase costs are managed. Project life cycles, techniques of cost estimation and cost management are examined. A survey was used to gather information by means of face-to-face and telephonic interviews, as well as an electronic questionnaire. The total population of entities in South Africa that conduct metallurgical research projects is small, numbering only 12 in all. The ten entities that conducted the largest metallurgical research projects in terms of average size were selected for this study. The conclusion drawn from the survey was that all costs over the life cycle of metallurgical research projects are not taken into account in the initial cost estimate of a project. Costs are mainly managed during the growth phase of a project and not during the introduction phase, when 80% of the costs are normally committed. The implication of this is that cost estimates for metallurgical research projects may not be accurate and costs are not necessarily managed properly throughout the life cycle of such projects. This may lead to cost overruns of project budgets, project budgets being depleted before the delivery stage and research sections running at a loss.http://www.unisa.ac.za/default.asp?Cmd=ViewContent&ContentID=22335am201