Randoop.NET vs Green comparison of testing frameworks
What are the differences between Randoop.NET and Green?

	Randoop.NET https://github.com/abb-iss/Randoop.NET	Green https://github.com/CleanCut/green
Programming language	.NET	Python
Category	Unit Testing	Unit Testing
General info	Randoop.NET is an API fuzzing unit test generator for .NET libraries. Randoop.NET creates test cases by a sequence of API method calls and it improves on random and static test generation by incorporating feedback during test generation.	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)
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	Yes Randoop.net is an xUnit style testing framework	No
Client-side Allows testing code execution on the client, such as a web browser	Yes You can test front-end components by testing individual front-end classes and modules	Yes It can test front-end components of the django framework
Server-side Allows testing the bahovior of a server-side code	Yes You can test back-end components by testing individual back-end classes and modules	Yes It can test server-side behaviours of web applications written with Python
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	Apache License 2.0	MIT License
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)	N/A	Yes Through the use of Python's mock library
Grouping Allows organizing tests in groups	Yes You can generate test suites with Randoop	N/A
Other Other useful information about the testing framework