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Database testing. Database testing usually consists of a layered process, including the user interface (UI) layer, the business layer, the data access layer and the database itself. The UI layer deals with the interface design of the database, while the business layer includes databases supporting business strategies .
Referential integrity is a property of data stating that all its references are valid. In the context of relational databases, it requires that if a value of one attribute (column) of a relation (table) references a value of another attribute (either in the same or a different relation), then the referenced value must exist. [1]
Database design. Database design is the organization of data according to a database model. The designer determines what data must be stored and how the data elements interrelate. With this information, they can begin to fit the data to the database model. [ 1] A database management system manages the data accordingly.
Chase (algorithm) The chase is a simple fixed-point algorithm testing and enforcing implication of data dependencies in database systems. It plays important roles in database theory as well as in practice. It is used, directly or indirectly, on an everyday basis by people who design databases, and it is used in commercial systems to reason ...
Smoke testing is also done by testers before accepting a build for further testing. Microsoft claims that after code reviews, "smoke testing is the most cost-effective method for identifying and fixing defects in software". [10] One can perform smoke tests either manually or using an automated tool. In the case of automated tools, the process ...
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.
All-pairs testing. In computer science, all-pairs testing or pairwise testing is a combinatorial method of software testing that, for each pair of input parameters to a system (typically, a software algorithm ), tests all possible discrete combinations of those parameters. Using carefully chosen test vectors, this can be done much faster than ...
In particular, three data sets are commonly used in different stages of the creation of the model: training, validation, and test sets. The model is initially fit on a training data set, [ 3] which is a set of examples used to fit the parameters (e.g. weights of connections between neurons in artificial neural networks) of the model. [ 4]