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Bean Validation defines a metadata model and API for JavaBean validation. The metadata source is annotations, with the ability to override and extend the meta-data through the use of XML validation descriptors. Originally defined as part of Java EE, version 2 aims to work in Java SE apps as well.
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]
System suitability – A test run each time an analysis is performed to ensure the test method is acceptable and is performing as written. This type of check is often run in a QC Lab. Usually, system suitability is performed by analyzing a standard material (House standard or reference standard) before the unknowns are run in an analytical method.
The Turing test is an informal validation method that was developed by the English mathematician Alan Turing in the 1950s, which at its roots is a specialized form of face validation because humans can be seen as "experts" on being able to analyze how other humans will respond in a given situation. Specifically, this model is best suited for ...
Overview of the monitor based verification process as described by Falcone, Havelund and Reger in A Tutorial on Runtime Verification. The broad field of runtime verification methods can be classified by three dimensions: [9] The system can be monitored during the execution itself (online) or after the execution e.g. in form of log analysis ...
Such final external validation requires the use of an acceptance test which is a dynamic test. However, it is also possible to perform internal static tests to find out if the software meets the requirements specification but that falls into the scope of static verification because the software is not running.
Verification and validation of computer simulation models is conducted during the development of a simulation model with the ultimate goal of producing an accurate and credible model. [ 1 ] [ 2 ] "Simulation models are increasingly being used to solve problems and to aid in decision-making.
Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]