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Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]
A classification of SQL injection attacking vector as of 2010. In computing, SQL injection is a code injection technique used to attack data-driven applications, in which malicious SQL statements are inserted into an entry field for execution (e.g. to dump the database contents to the attacker).
Salesforce management systems (also sales force automation systems (SFA)) are information systems used in customer relationship management (CRM) marketing and management that help automate some sales and sales force management functions. They are often combined with a marketing information system, in which case they are often called CRM systems.
Code injection is a computer security exploit where a program fails to correctly process external data, such as user input, causing it to interpret the data as executable commands. An attacker using this method "injects" code into the program while it is running.
A check constraint is a type of integrity constraint in SQL which specifies a requirement that must be met by each row in a database table. The constraint must be a predicate . It can refer to a single column, or multiple columns of the table.
Validation during the software development process can be seen as a form of User Requirements Specification validation; and, that at the end of the development process is equivalent to Internal and/or External Software validation. Verification, from CMMI's point of view, is evidently of the artifact kind.
Member checks can be used as a technique to evaluate the problems with the study process such as practical, theoretical, representational, and moral flaws to ensure the honesty of the research procedures. [19] The process of a member check also is important in revealing missing information that should be addressed before concluding the study.
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]