Expert estimation: The quantification step, i.e., the step where the estimate is produced based on judgmental processes.The top level categories are the following: There are many ways of categorizing estimation approaches, see for example. The estimation approaches based on functionality-based size measures, e.g., function points, is also based on research conducted in the 1970s and 1980s, but are re-calibrated with modified size measures and different counting approaches, such as the use case points or object points in the 1990s. They have their basis in estimation research conducted in the 1970s and 1980s and are since then updated with new calibration data, with the last major release being COCOMO II in the year 2000. The perhaps most common estimation methods today are the parametric estimation models COCOMO, SEER-SEM and SLIM. Since then a high number of model building approaches have been evaluated, such as approaches founded on case-based reasoning, classification and regression trees, simulation, neural networks, Bayesian statistics, lexical analysis of requirement specifications, genetic programming, linear programming, economic production models, soft computing, fuzzy logic modeling, statistical bootstrapping, and combinations of two or more of these models. The early models were typically based on regression analysis or mathematically derived from theories from other domains.
#COCOMO MODEL WIKI SOFTWARE#
Most of the research has focused on the construction of formal software effort estimation models. Software researchers and practitioners have been addressing the problems of effort estimation for software development projects since at least the 1960s see, e.g., work by Farr and Nelson. This is believed to be unfortunate, because communication problems may occur and because the concepts serve different goals. Ĭurrently the term “effort estimate” is used to denote as different concepts such as most likely use of effort (modal value), the effort that corresponds to a probability of 50% of not exceeding (median), the planned effort, the budgeted effort or the effort used to propose a bid or price to the client.
#COCOMO MODEL WIKI PROFESSIONAL#
The strong overconfidence in the accuracy of the effort estimates is illustrated by the finding that, on average, if a software professional is 90% confident or “almost sure” to include the actual effort in a minimum-maximum interval, the observed frequency of including the actual effort is only 60-70%. However, the measurement of estimation error is problematic, see Assessing the accuracy of estimates. For a review of effort estimation error surveys, see. The mean effort overrun seems to be about 30% and not decreasing over time. Typically, effort estimates are over-optimistic and there is a strong over-confidence in their accuracy. Published surveys on estimation practice suggest that expert estimation is the dominant strategy when estimating software development effort. 8 Comparison of development estimation software.