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Database normalization is the process of structuring a relational database accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .
Data redundancy leads to data anomalies and corruption and generally should be avoided by design; [5] applying database normalization prevents redundancy and makes the best possible usage of storage. [ 6 ]
"Don't repeat yourself" (DRY), also known as "duplication is evil", is a principle of software development aimed at reducing repetition of information which is likely to change, replacing it with abstractions that are less likely to change, or using data normalization which avoids redundancy in the first place.
ISO/IEC/IEEE 29119 Software and systems engineering -- Software testing [1] is a series of five international standards for software testing.First developed in 2007 [2] and released in 2013, the standard "defines vocabulary, processes, documentation, techniques, and a process assessment model for testing that can be used within any software development lifecycle."
Software testing can provide objective, independent information about the quality of software and the risk of its failure to a user or sponsor. [1] Software testing can determine the correctness of software for specific scenarios but cannot determine correctness for all scenarios. [2] [3] It cannot find all bugs.
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 .
Data reduction is the transformation of numerical or alphabetical digital information derived empirically or experimentally into a corrected, ordered, and simplified form. . The purpose of data reduction can be two-fold: reduce the number of data records by eliminating invalid data or produce summary data and statistics at different aggregation levels for various applications
Delta encoding is a way of storing or transmitting data in the form of differences (deltas) between sequential data rather than complete files; more generally this is known as data differencing. Delta encoding is sometimes called delta compression, particularly where archival histories of changes are required (e.g., in revision control software).