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External validity is the validity of applying the conclusions of a scientific study outside the context of that study. [1] In other words, it is the extent to which the results of a study can generalize or transport to other situations, people, stimuli, and times.
External validation happens when it is performed by asking the stakeholders if the software meets their needs. Different software development methodologies call for different levels of user and stakeholder involvement and feedback; so, external validation can be a discrete or a continuous event.
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.
This emphasis was designed to address a core requirement that validation include some demonstration that the test measures the theoretical construct it purported to measure. Construct validity has three aspects or components: the substantive component, structural component, and external component. [15]
And, validation (of the whole software product) would be equivalent to dynamic testing and intended to be applied to the running software product (not its artifacts, except requirements). Notice that requirements validation can be performed statically and dynamically (See artifact validation).
Ecological validity, the ability to generalize study findings to the real world, is a subcategory of external validity. [ 6 ] Another example highlighting the differences between these terms is from an experiment that studied pointing [ 7 ] —a trait originally attributed uniquely to humans—in captive chimpanzees.
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In other words, the relevance of external and internal validity to a research study depends on the goals of the study. Furthermore, conflating research goals with validity concerns can lead to the mutual-internal-validity problem, where theories are able to explain only phenomena in artificial laboratory settings but not the real world.