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Spring Boot is a convention-over-configuration extension for the Spring Java platform intended to help minimize configuration concerns while creating Spring-based applications. [ 4 ] [ 5 ] The application can still be adjusted for specific needs, but the initial Spring Boot project provides a preconfigured "opinionated view" of the best ...
Verification is intended to check that a product, service, or system meets a set of design specifications. [6] [7] In the development phase, verification procedures involve performing special tests to model or simulate a portion, or the entirety, of a product, service, or system, then performing a review or analysis of the modeling results.
Spring Framework 4.0 was released in December 2013. [10] Notable improvements in Spring 4.0 included support for Java SE (Standard Edition) 8, Groovy 2, [11] [12] some aspects of Java EE 7, and WebSocket. [13] Spring Framework 4.2.0 was released on 31 July 2015 and was immediately upgraded to version 4.2.1, which was released on 01 Sept 2015. [14]
In computer programming, an enumerated type (also called enumeration, enum, or factor in the R programming language, and a categorical variable in statistics) is a data type consisting of a set of named values called elements, members, enumeral, or enumerators of the type.
XSD (XML Schema Definition), a recommendation of the World Wide Web Consortium , specifies how to formally describe the elements in an Extensible Markup Language document. It can be used by programmers to verify each piece of item content in a document, to assure it adheres to the description of the element it is placed in. [ 1 ]
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
If the mean of the model is μ m and the mean of system is μ s then the difference between the model and the system is D = μ m - μ s. The hypothesis to be tested is if D is within the acceptable range of accuracy. Let L = the lower limit for accuracy and U = upper limit for accuracy. Then H 0 L ≤ D ≤ U. versus H 1 D < L or D > U. is to ...
Another approach is deductive verification. [5] [6] It consists of generating from the system and its specifications (and possibly other annotations) a collection of mathematical proof obligations, the truth of which imply conformance of the system to its specification, and discharging these obligations using either proof assistants (interactive theorem provers) (such as HOL, ACL2, Isabelle ...