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Evidence-based Scheduling
Evidence-based scheduling is a software estimation approach created by Joel Spolsky, a commentator on software engineering principles. Evidence-based Scheduling is based on at least two core ideas: including all time spent, and using a Monte Carlo completion date prediction method. Evidence-based scheduling is an example of an evidence-based practice. Including all time spent One of the core ideas of evidence-based scheduling, that adds to the normal estimation practices, is the idea of including all time spent, regardless of relevance. Most people, when estimating, measure the time they actually spend on a project – classic Time Accounting categories such as cited in McConnell's ''Software Project Survival Guide'' do not allow for accounting for non-project activities. While McConnell goes on to include less obvious activities such as holidays, sick days and project support, he and most others identify such as activities to be separately recorded. However, recording and att ...
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Software Estimation
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. Methods Methods for estimation in software engineering include these principles: *Analysis effort method *Parametric Estimating * The Planning Game (from Extreme Programming) * ITK method, also known as Method CETIN * Proxy-based estimating (PROBE) (from the Personal Software Process) *Program Evaluation and Review Technique (PERT) *Putnam_model, also known as SLIM *PRICE Systems Founders of Commercial Parametric models that estimates the scope, cost, effort and schedule for software projects. *SEER-SEM Parametric Estimation of Effort, Schedule, Cost, Risk. Minimum time and staffing concepts based on Brooks's law * The Use Case Points met ...
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Joel Spolsky
Avram Joel Spolsky (born 1965) is a software engineer and writer. He is the author of ''Joel on Software'', a blog on software development, and the creator of the project management software Trello. He was a Program Manager on the Microsoft Excel team between 1991 and 1994. He later founded Fog Creek Software in 2000 and launched the ''Joel on Software'' blog. In 2008, he launched the Stack Overflow programmer Q&A site in collaboration with Jeff Atwood. Using the Stack Exchange software product which powers Stack Overflow, the Stack Exchange Network now hosts over 170 Q&A sites. Biography Spolsky was born to Jewish parents and grew up in Albuquerque, New Mexico, and lived there until he was 15. He then moved with his family to Israel, where he attended high school and completed his military service in the Paratroopers Brigade. He was one of the founders of the kibbutz Hanaton in Lower Galilee. In 1987, he returned to the United States to attend college. He studied at the Univer ...
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Evidence-based Practice
Evidence-based practice (EBP) is the idea that occupational practices ought to be based on scientific evidence. While seemingly obviously desirable, the proposal has been controversial, with some arguing that results may not specialize to individuals as well as traditional practices. Evidence-based practices have been gaining ground since the formal introduction of evidence-based medicine in 1992 and have spread to the allied health professions, education, management, law, public policy, architecture, and other fields. In light of studies showing problems in scientific research (such as the replication crisis), there is also a movement to apply evidence-based practices in scientific research itself. Research into the evidence-based practice of science is called metascience. The movement towards evidence-based practices attempts to encourage and, in some instances, require professionals and other decision-makers to pay more attention to evidence to inform their decision-making. ...
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Monte Carlo Method
Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches. Monte Carlo methods are mainly used in three problem classes: optimization, numerical integration, and generating draws from a probability distribution. In physics-related problems, Monte Carlo methods are useful for simulating systems with many coupled degrees of freedom, such as fluids, disordered materials, strongly coupled solids, and cellular structures (see cellular Potts model, interacting particle systems, McKean–Vlasov processes, kinetic models of gases). Other examples include modeling phenomena with significant uncertainty in inputs such as the calculation of ris ...
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Software Engineering Costs
Software is a set of computer programs and associated documentation and data. This is in contrast to hardware, from which the system is built and which actually performs the work. At the lowest programming level, executable code consists of machine language instructions supported by an individual processor—typically a central processing unit (CPU) or a graphics processing unit (GPU). Machine language consists of groups of binary values signifying processor instructions that change the state of the computer from its preceding state. For example, an instruction may change the value stored in a particular storage location in the computer—an effect that is not directly observable to the user. An instruction may also invoke one of many input or output operations, for example displaying some text on a computer screen; causing state changes which should be visible to the user. The processor executes the instructions in the order they are provided, unless it is instructed ...
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