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Contributing

We encourage contribution from the open source community to make DataGenerator better. Please refer to the development page for more information on how to contribute to this project.

Building

DataGenerator uses Maven for build. Please install Maven by downloading it from here.

# Clone DataGenerator git repo
git clone git://github.com/FINRAOS/DataGenerator.git
cd DataGenerator

# Checkout master branch
git checkout master

# Run package to compile and create jar (also runs unit tests)
mvn package

# Compile and run unit tests only
mvn test

DataGenerator Class architecture diagram

DataGenerator class diagram

(NOTE: This does not include all classes included in the DataGenerator package)

License Type

The DataGenerator project is licensed under Apache License Version 2.0

======= DataGenerator

Primary goals of test automation should be increased coverage, decreased manual effort and flexibility to accommodate changing requirements. DataGenerator is a new testing tool that supports these goals. This tool supports requirements specification and test case specification in terms of work flows and data equivalence classes. By using templates, the format of the test data produced is highly customizable, and has the ability to include dynamically calculated test expectations. The combined use of straightforward specification inputs, tool-assured test case coverage, and customizable output enables a tester to achieve increased coverage in less time, while maintaining the flexibility to adapt to requirements changes. In an agile software development environment, modifications to the specification input and output templates are all that’s required to get the tests re-generated. This reduces time spent on test case generation and requirements gathering and alleviates gaps between requirements and test cases generated which strengthens behavior-driven development.

About

DataGenerator is a testing tool that allows the user to model the behavior of a piece of software by employing specification and dependency modeling. Using templates, it enables the user to produce highly customizable and dynamically calculated test expectations, test data or test scripts to help verify software.

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