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PyCharm – Cross-platform Python IDE with code inspections available for analyzing code on-the-fly in the editor and bulk analysis of the whole project. PyDev – Eclipse-based Python IDE with code analysis available on-the-fly in the editor or at save time. Pylint – Static code analyzer. Quite stringent; includes many stylistic warnings as ...
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 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]
A cyclic redundancy check (CRC) is an error-detecting code commonly used in digital networks and storage devices to detect accidental changes to digital data. [ 1 ] [ 2 ] Blocks of data entering these systems get a short check value attached, based on the remainder of a polynomial division of their contents.
The validation may be strict (such as rejecting any address that does not have a valid postal code), or with fuzzy or approximate string matching (such as correcting records that partially match existing, known records). Some data cleansing solutions will clean data by cross-checking with a validated data set.
Validation: "Are we trying to make the right thing?", i.e., is the product specified to the user's actual needs? Verification : "Have we made what we were trying to make?", i.e., does the product conform to the specifications?
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]
Translation validation can be used even with a compiler that sometimes generates incorrect code, as long as this incorrect does not manifest itself for a given program. Depending on the input program the translation validation can fail (because the generated code is wrong or the translation validation technique is too weak to show correctness).