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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]
Software validation checks that the software product satisfies or fits the intended use (high-level checking), i.e., the software meets the user requirements, not as specification artifacts or as needs of those who will operate the software only; but, as the needs of all the stakeholders (such as users, operators, administrators, managers ...
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.
The aim of software dynamic verification is to find the errors introduced by an activity (for example, having a medical software to analyze bio-chemical data); or by the repetitive performance of one or more activities (such as a stress test for a web server, i.e. check if the current product of the activity is as correct as it was at the ...
Program repair is performed with respect to an oracle, encompassing the desired functionality of the program which is used for validation of the generated fix. A simple example is a test-suite—the input/output pairs specify the functionality of the program.
Inspection is a verification method that is used to compare how correctly the conceptual model matches the executable model. Teams of experts, developers, and testers will thoroughly scan the content (algorithms, programming code, documents, equations) in the original conceptual model and compare with the appropriate counterpart to verify how closely the executable model matches. [1]
Examples of oracles include specifications, contracts, [4] comparable products, past versions of the same product, inferences about intended or expected purpose, user or customer expectations, relevant standards, and applicable laws. Software testing is often dynamic in nature; running the software to verify actual output matches expected.
Non-functional validation(e.g. performance testing) Differences between a conference room pilot and a formal UAT: It is attempting to identify how well the application meets business needs, and identify gaps, whilst still in the design phase of the project; There is an expectation that changes will be required before acceptance of the solution