valideringstekniker

Valideringstekniker are methods used to determine whether a product, system, or model achieves its intended use and provides credible results in its operating context. The term is used across disciplines such as software engineering, statistics, measurement science and regulated industries. In practice, validation focuses on fitness for purpose rather than conformance to specifications, distinguished from verification.

In software and systems engineering, valideringsteknikker include acceptance testing, system testing, field testing, beta testing and pilot deployments. They assess whether the software supports the tasks and user needs it is intended to enable, often through end-to-end scenarios and real-world demonstrations. Usability testing and user trials are common.

In statistics and measurement science, validation refers to establishing that a measurement instrument or a statistical model measures what it intends to measure. Methods include content validity, construct validity and criterion validity, as well as calibration and reliability studies.

In data science and machine learning, validation is used to estimate how the model will perform on new data. Techniques include train-test splits, cross-validation (k-fold and stratified), hold-out sets, bootstrapping, and nested cross-validation for hyperparameter tuning. Calibration of probability estimates and metrics such as accuracy, precision, recall and AUC are common.

In regulated and manufacturing contexts, validation encompasses process validation and equipment qualification (IQ/OQ/PQ) to ensure operations remain in a validated state. Documentation, traceability, change control and independent review are emphasized, with standards defined by industry regulators.

Good practice emphasizes preregistration of validation plans, reproducibility and transparent reporting.