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The V-model is a graphical representation of a systems development lifecycle. It is used to produce rigorous development lifecycle models and project management models. The V-model falls into three broad categories, the German V-Modell, a general testing model, and the US government standard. [2]
In software development, the V-model [2] represents a development process that may be considered an extension of the waterfall model and is an example of the more general V-model. Instead of moving down linearly, the process steps are bent upwards after the coding phase, to form the typical V shape.
For example, the Document Object Model (DOM) is a collection of objects that represent a page in a web browser, used by script programs to examine and dynamically change the page. There is a Microsoft Excel object model [1] for controlling Microsoft Excel from another program, and the ASCOM Telescope Driver is an object model for controlling an ...
In a standardized open-ended interview, the same open-ended questions are asked to all interviewees. This approach facilitates faster interviews that can be more easily analyzed and compared. In a closed fixed-response interview, all interviewees are asked the same questions and asked to choose answers from among the same set of alternatives.
Here is an example of a cylinder as given in VPython's documentation (in older VPython implementations, the module to import is vpython, not visual): from visual import * # Import the visual module rod = cylinder ( pos = ( 0 , 2 , 1 ), axis = ( 5 , 0 , 0 ), radius = 1 )
By using visual models complex ideas are not held to human limitations, allowing for greater complexity without a loss of comprehension. [1] Visual modeling can also be used to bring a group to a consensus. Models help effectively communicate ideas among designers, allowing for quicker discussion and an eventual consensus. [2]
A computational model uses computer programs to simulate and study complex systems [1] using an algorithmic or mechanistic approach and is widely used in a diverse range of fields spanning from physics, [2] engineering, [3] chemistry [4] and biology [5] to economics, psychology, cognitive science and computer science.
A foundation model, also known as large X model (LxM), is a machine learning or deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. [1] Generative AI applications like Large Language Models are often examples of foundation models.