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[1] [2] When used to determine if a computer program should be subjected to further, more fine-grained testing, a smoke test may be called a pretest [5] or an intake test. [1] Alternatively, it is a set of tests run on each new build of a product to verify that the build is testable before the build is released into the hands of the test team ...
Test coverage refers to the percentage of software requirements that are tested by black-box testing for a system or application. [7] This is in contrast with code coverage, which examines the inner workings of a program and measures the degree to which the source code of a program is executed when a test suite is run. [8]
One agile practice, test-driven software development (TDD), is a way of unit testing such that unit-level testing is performed while writing the product code. [69] Test code is updated as new features are added and failure conditions are discovered (bugs fixed).
"A/B testing" is a shorthand for a simple randomized controlled experiment, in which a number of samples (e.g. A and B) of a single vector-variable are compared. [1] A/B tests are widely considered the simplest form of controlled experiment, especially when they only involve two variants.
Unit is defined as a single behaviour exhibited by the system under test (SUT), usually corresponding to a requirement [definition needed].While it may imply that it is a function or a module (in procedural programming) or a method or a class (in object-oriented programming) it does not mean functions/methods, modules or classes always correspond to units.
Also simply application or app. Computer software designed to perform a group of coordinated functions, tasks, or activities for the benefit of the user. Common examples of applications include word processors, spreadsheets, accounting applications, web browsers, media players, aeronautical flight simulators, console games, and photo editors. This contrasts with system software, which is ...
The common practice of allowing a 5-10 percent margin for late execution reduces the potential number of false negatives in test execution. It is also suggested to treat test code with the same respect as production code. Test code must work correctly for both positive and negative cases, last a long time, and be readable and maintainable.
In 1981, Duran and Ntafos formally investigated the effectiveness of testing a program with random inputs. [23] [24] While random testing had been widely perceived to be the worst means of testing a program, the authors could show that it is a cost-effective alternative to more systematic testing techniques.