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Pytest. 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.
MIT. 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.
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.
Test double. A test double is software used in software test automation that satisfies a dependency so that the test need not depend on production code. A test double provides functionality via an interface that the software under test cannot distinguish from production code. A programmer generally uses a test double to isolate the behavior of ...
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.
Mock objects have the same interface as the real objects they mimic, allowing a client object to remain unaware of whether it is using a real object or a mock object. Many available mock object frameworks allow the programmer to specify which methods will be invoked on a mock object, in what order, what parameters will be passed to them, and what values will be returned.
System under test (SUT) refers to a system that is being tested for correct operation. According to ISTQB it is the test object. [1][2][3] From a unit testing perspective, the system under test represents all of the classes in a test that are not predefined pieces of code like stubs or even mocks. Each one of this can have its own configuration ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]