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

stestr

https://pypi.org/project/stestr/

HavaRunner

https://github.com/havarunner/havarunner
Programming language

Python

Java

Category

Unit Testing

Unit 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.

HavaRuner is a Java test framework with built-in concurrency support, suites and scenarios

HavaRunner is a Java test framework that has built in support for concurrency and enables you to create suites. You can run the same test against multiple scenarios and speeds up development cycles with faster tests.HavaRunner is a JUnit runner, which means that it is built on top of JUnit it's fairly straightforward to adopt it in a codebase that already has JUnit tests.
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

You can test front-end functionality and components with havarunner
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

HavaRunner is able to test server side functions and components
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

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

Grouping
Allows organizing tests in groups

N/A

Yes

You can group your tests by annotating them as @PartOf a suite
Other
Other useful information about the testing framework