Explore: Validation Methodologies

In computing, data validation or input validation is the process of ensuring data has undergone data cleansing to confirm it has data quality, that is

pre-silicon methodologies. As a result, a number of functional bugs survive into manufactured silicon, and it is the job of post-silicon validation to detect

models validation must be mainly for robustness, prediction performances and applicability domain (AD) of the models. Some validation methodologies can be

hand, software validation is: "Was X what we should have built? Does X meet the high-level requirements?" Verification and validation are not the same

words "verification" and "validation" are sometimes preceded with "independent", indicating that the verification and validation is to be performed by a

Cross-validation, sometimes called rotation estimation or out-of-sample testing, is any of various similar model validation techniques for assessing how

researchers distinguish methods from methodologies by holding that methods are modes of data collection while methodologies are more general research strategies

validation; and addresses such areas as: development and maintenance of security metrics, security evaluation criteria and evaluation methodologies,

and statistical validation are different aspects of validation. A discrete-event simulation framework approach for the validation of agent-based systems

analysis Group concept mapping Validation and verification Varimax rotation Van Exel NJA, G de Graaf. 2005: "Q methodology: A sneak preview" (PDF). Archived