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Effort estimation often requires generalizing from a small number of historical projects. Generalization from such limited experience is an inherently underconstrained problem. Hence, the learned effort models can exhibit large deviations that prevent standard statistical methods (e.g., t-tests) from distinguishing the performance of alternative(More)
COCONUT calibrates effort estimation models using an ex-haustive search over the space of calibration parameters in a COCOMO I model. This technique is much simpler than other effort estimation method yet yields PRED levels com-parable to those other methods. Also, it does so with less project data and fewer attributes (no scale factors). How-ever, a(More)
There exists a large and growing number of proposed estimation methods but little conclusive evidence ranking one method over another. Prior effort estimation studies suffered from “conclusion instability”, where the rankings offered to different methods were not stable across (a) different evaluation criteria; (b) different data sources; or (c) different(More)
<b><i>Background:</i></b> Size features such as lines of code and function points are deemed essential for effort estimation. No one questions under what conditions size features are actually a "must". <b><i>Aim:</i></b> To question the need for size features and to propose a method that compensates their absence. <b><i>Method:</i></b> A baseline(More)
Often repositories of systems engineering artifacts at NASA's Jet Propulsion Laboratory (JPL) are so large and poorly structured that they have outgrown our capability to effectively manually process their contents to extract useful information. Sophisticated text mining methods and tools seem a quick, low-effort approach to automating our limited manual(More)
This paper deseribes a survey conducted of the staff of the Jet Propulsion Laboratory (JPL) who estimate software costs for software intensive projects in JPL’s teehnical divisions. Respondents to the survey deseribed what techniques they use in estimation of software costs and, in an experiment, each respondent estimated the size and cost of a speeiflc(More)
Delta estimation uses changes to old projects to estimate new projects. Delta estimation assumes that new costs can be extrapolated from old projects. In this study, we show that in certain real-world data sets. there exists attributes where this assumption does not hold. We define here an automatic method to find which attributes can be safely used for(More)
Adoption of advanced automated SE (ASE) tools would be favored if a business case could be made that these tools are more valuable than alternate methods. In theory, software prediction models can be used to make that case. In practice, this is complicated by the "local tuning" problem. Normally, predictors for software effort and defects and threat use(More)
Before performing drastic changes to a project, it is worthwhile to thoroughly explore the available options within the current structure of a project. An alternative to drastic change are internal changes that adjust current options within a software project. In this paper, we show that the effects of numerous internal changes can out-weigh the effects of(More)