That means typing related bugs that could potentially be found in advance lead to run time exceptions. Using XML does not make it easy to enforce these types. Data schemas, for instance, are inherently typed, that is fields have types and records in turn consist of typed fields. But the use of XML also has its shortcomings. For the most part using XML works just fine there is no need for an IDE or compiler tool-chain, the programs are verbose such that they can be understood by other people, and XML as a language is standardized and well-defined, which means there is a plethora of tools available aiding in the creation of XML documents.
#JAVA TEST DATA GENERATOR GENERATOR#
The current way for developing such data generator programs involves writing schema specifications in XML. For that PDGF provides an XML-based specification language and many generators, e.g., long number generator or data time generator, that can be used to specify a custom schema and along the logic and rules for generating test data for this particular schema. The main goal of PDGF is to provide the means to create massively parallel and scalable data generation programs without the need of any low-level programming. For that reason bankmark UG (haftungsbeschränkt) has developed the Parallel Data Generator Framework (PDGF). With the current rise of Machine Learning libraries and frameworks as well as general data processing and data analytics engines there is bigger and bigger need for good quality test data.
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