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

	Crosscheck https://github.com/cross-check/cross-check	stestr https://pypi.org/project/stestr/
Programming language	JavaScript	Python
Category	Unit Testing	Unit Testing
General info	Crosscheck is a JavaScript unit-testing framework capable of emulating multiple browser environments Crosscheck is an open source testing framework for verifying your in-browser JavaScript. It helps you ensure that your code will run in many different browsers such as Internet Explorer, Chrome and Firefox, but without needing installations of those browsers. The only thing you need is a Java Virtual Machine.	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.
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	N/A	No
Client-side Allows testing code execution on the client, such as a web browser	No	Yes Stestr being a test runner that runs unittest tests, it can test fron-tend functionality and behaviour.
Server-side Allows testing the bahovior of a server-side code	Yes Crosscheck is used to verify in-browser JavaScript and is a headless test framework, it tests back-end components and functionality	Yes Stestr being a test runner that runs unittest tests, it can run back-end tests for functionality and 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	Yes By use of a third party library like Fixture
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	By use of a third party library like Fixture
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	Yes By using a library like test-generator
Licence Licence type governing the use and redistribution of the software	N/A	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)	N/A	N/A
Grouping Allows organizing tests in groups	N/A	N/A
Other Other useful information about the testing framework