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Software development effort estimation. In software development, effort estimation is the process of predicting the most realistic amount of effort (expressed in terms of person-hours or money) required to develop or maintain software based on incomplete, uncertain and noisy input.
Estimation (project management) In project management (e.g., for engineering ), accurate estimates are the basis of sound project planning. Many processes have been developed to aid engineers in making accurate estimates, such as. Analogy based estimation.
e. The Delphi method or Delphi technique (/ ˈdɛlfaɪ / DEL-fy; also known as Estimate-Talk-Estimate or ETE) is a structured communication technique or method, originally developed as a systematic, interactive forecasting method that relies on a panel of experts. [1][2][3][4][5] Delphi has been widely used for business forecasting and has ...
Planning poker. Planning poker, also called Scrum poker, is a consensus-based, gamified technique for estimating, mostly used for timeboxing in Agile principles. In planning poker, members of the group make estimates by playing numbered cards face-down to the table, instead of speaking them aloud. The cards are revealed, and the estimates are ...
Cost estimation in software engineering is typically concerned with the financial spend on the effort to develop and test the software, this can also include requirements review, maintenance, training, managing and buying extra equipment, servers and software. Many methods have been developed for estimating software costs for a given project.
The Putnam model is an empirical software effort estimation model. [1] The original paper by Lawrence H. Putnam published in 1978 is seen as pioneering work in the field of software process modelling. [2] As a group, empirical models work by collecting software project data (for example, effort and size) and fitting a curve to the data.
Gigerenzer & Gaissmaier (2011) state that sub-sets of strategy include heuristics, regression analysis, and Bayesian inference. [14]A heuristic is a strategy that ignores part of the information, with the goal of making decisions more quickly, frugally, and/or accurately than more complex methods (Gigerenzer and Gaissmaier [2011], p. 454; see also Todd et al. [2012], p. 7).
Numerical differentiation. Finite difference estimation of derivative. In numerical analysis, numerical differentiation algorithms estimate the derivative of a mathematical function or function subroutine using values of the function and perhaps other knowledge about the function.