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

	stestr https://pypi.org/project/stestr/	Specter http://specter.sourceforge.net/
Programming language	Python	.NET
Category	Unit Testing	Acceptance Testing
General info	stestr is a Python test runner designed to execute unittest test suites stestr executes unittest test suites by using multiple processes to split up execution of a test suite then stores a history of all test runs to help in debugging failures and optimizing the scheduler to improve speed.	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 Stestr being a test runner that runs unittest tests, it can test fron-tend functionality and behaviour.	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 Stestr being a test runner that runs unittest tests, it can run back-end tests for functionality and behaviour.	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	Yes By use of a third party library like Fixture	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.	By use of a third party library like Fixture	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.	Yes By using a library like test-generator	N/A
Licence Licence type governing the use and redistribution of the software	Apache License 2.0	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)	N/A	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