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By default, Spring boot provides embedded web servers (such as Tomcat) out-of-the-box. [21] However, Spring Boot can also be deployed as a WAR file on a standalone WildFly application server. [22] If Maven is used as the build tool, there is a wildfly-maven-plugin Maven plugin that allows for automatic deployment of the generated WAR file. [22]
The Spring Framework is an application framework and inversion of control container for the Java platform. [2] The framework's core features can be used by any Java application, but there are extensions for building web applications on top of the Java EE (Enterprise Edition) platform.
In 2005 the project was introduced into the Spring portfolio by Keith Donald and grew into the official Spring sub-project it is now. The first production ready 1.0 release was made on 2006-10-26. Version 2.0, first released on 2008-04-29, saw a major internal reorganization of the framework to allow better integration with JavaServer Faces .
The structure of an application with PAC. Presentation–abstraction–control (PAC) is a software architectural pattern.It is an interaction-oriented software architecture, and is somewhat similar to model–view–controller (MVC) in that it separates an interactive system into three types of components responsible for specific aspects of the application's functionality.
Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes:
Hierarchical model–view–controller (HMVC) is a software architectural pattern, a variation of model–view–controller (MVC) similar to presentation–abstraction–control (PAC), that was published in 2000 in an article [1] in JavaWorld Magazine. The authors were apparently unaware of PAC, which was published 13 years earlier.
Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points.
Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.