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

	Green https://github.com/CleanCut/green	Specter http://specter.sourceforge.net/
Programming language	Python	.NET
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)	Specter is a behaviour-driven development framework for .NET and Mono Specter enables behavior driven development (BDD) by allowing developers to write executable specifications for their objects, before actually implementing them, this is similar to test driven development however the different nomenclature makes it different from writing 'tests' for code that does not exist yet
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 Developers can create specfications of the expected front-end behaviours and test them
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 Yes developers can create specfications of the expected back-end behaviours and test these.
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	BSD 3-Clause 'New' or 'Revised' 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)	Yes Through the use of Python's mock library	N/A
Grouping Allows organizing tests in groups	N/A	Yes You can create your own test suites with specter
Other Other useful information about the testing framework