Green vs JDave comparison of testing frameworks
What are the differences between Green and JDave?

	Green https://github.com/CleanCut/green	JDave http://jdave.org/
Programming language	Python	Java
Category	Unit Testing	Acceptance Testing
General info	Green is a clean, colorful, fast Python test runner This is a test runner that has pretty printing on output that makes results easy to read and understand. Some of its features include: Tests running in independent processes (fast), low redundancy in output (clean), supports pretty printing that is the terminal output, makes good use of color when the terminal supports it (colorful)	JDave is a BDD framework for Java JDave is inspired by RSpec and integrates JMock 2 as mocking framework and Hamcrest as matching library. It uses JUnit adapter to launch JDave specifications. This way it is possible to have IDE, build tool and coverage tool support from day one.
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	No
Client-side Allows testing code execution on the client, such as a web browser	Yes It can test front-end components of the django framework	Yes Front-end behaviour can be tested with JDave
Server-side Allows testing the bahovior of a server-side code	Yes It can test server-side behaviours of web applications written with Python	Yes JDave can test server-side behaviour
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	N/A	N/A
Group fixtures Allows defining a fixed, specific states of data for a group of tests (group-fixtures). This ensures specific environment for a given group of tests.	N/A	N/A
Generators Supports data generators for tests. Data generators generate input data for test. The test is then run for each input data produced in this way.	N/A	N/A
Licence Licence type governing the use and redistribution of the software	MIT License	Apache License 2.0
Mocks Mocks are objects that simulate the behavior of real objects. Using mocks allows testing some part of the code in isolation (with other parts mocked when needed)	Yes Through the use of Python's mock library	Yes It integrates JMock 2 as mocking framework
Grouping Allows organizing tests in groups	N/A	Yes Specifications can be grouped by tagging them with @Group annotation.
Other Other useful information about the testing framework