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Definition. The Test and Evaluation Master Plan documents the overall structure and objectives of the Test & Evaluation for a program. [3] It covers activities over a program’s life-cycle and identifies evaluation criteria for the testers. [4] The test and evaluation master plan consists of individual tests. Each test contains the following.
e. 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 tests is to write ...
A test strategy is an outline that describes the testing approach of the software development cycle. The purpose of a test strategy is to provide a rational deduction from organizational, high-level objectives to actual test activities to meet those objectives from a quality assurance perspective. The creation and documentation of a test ...
Session-based testing is a software test method that aims to combine accountability and exploratory testing to provide rapid defect discovery, creative on-the-fly test design, management control and metrics reporting. The method can also be used in conjunction with scenario testing. Session-based testing was developed in 2000 by Jonathan and ...
Operational acceptance testing (OAT) is used to conduct operational readiness (pre-release) of a product, service or system as part of a quality management system. OAT is a common type of non-functional software testing, used mainly in software development and software maintenance projects. This type of testing focuses on the operational ...
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.
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 ...
Level Test Design (LTD): Detailing test cases and the expected results as well as test pass criteria. Level Test Case (LTC): Specifying the test data for use in running the test cases identified in the Level Test Design. Level Test Procedure (LTPr): Detailing how to run each test, including any set-up preconditions and the steps that need to be ...