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Website. pytest.org. Pytest is a Python testing framework that originated from the PyPy project. It can be used to write various types of software tests, including unit tests, integration tests, end-to-end tests, and functional tests. Its features include parametrized testing, fixtures, and assert re-writing.
Unit testing is the cornerstone of extreme programming, which relies on an automated unit testing framework. This automated unit testing framework can be either third party, e.g., xUnit, or created within the development group. Extreme programming uses the creation of unit tests for test-driven development.
Software development. Test-driven development (TDD) is a way of writing code that involves writing an automated unit-level test case that fails, then writing just enough code to make the test pass, then refactoring both the test code and the production code, then repeating with another new test case. Alternative approaches to writing automated ...
Coding best practices or programming best practices are a set of informal, sometimes personal, rules (best practices) that many software developers, in computer programming follow to improve software quality. [1] Many computer programs require being robust and reliable for long periods of time, [2] so any rules need to facilitate both initial ...
Python. PyCharm – Cross-platform Python IDE with code inspections available for analyzing code on-the-fly in the editor and bulk analysis of the whole project. PyDev – Eclipse-based Python IDE with code analysis available on-the-fly in the editor or at save time. Pylint – Static code analyzer.
A Micro Unit testing framework for C/C++. At ~1k lines of code, it is simpler, lighter and much faster than heavier frameworks like Googletest and Catch2. Includes a rich set of assertion macros, supports automatic test registration and can output to multiple formats, like the TAP format or JUnit XML.
A test data set is a data set that is independent of the training data set, but that follows the same probability distribution as the training data set. If a model fit to the training data set also fits the test data set well, minimal overfitting has taken place (see figure below). A better fitting of the training data set as opposed to the ...
A/B testing (also known as bucket testing, split-run testing, or split testing) is a user experience research method. [1] A/B tests consist of a randomized experiment that usually involves two variants (A and B), [ 2 ] [ 3 ] [ 4 ] although the concept can be also extended to multiple variants of the same variable.