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Spec Explorer [1] is a Model-Based Testing (MBT [2] [3]) tool from Microsoft.It extends the Visual Studio Integrated Development Environment with the ability to define a model describing the expected behavior of a software system.
Model-based testing is an application of model-based design for designing and optionally also executing artifacts to perform software testing or system testing. Models can be used to represent the desired behavior of a system under test (SUT), or to represent testing strategies and a test environment.
Linear-on-the-fly testing, often referred to as LOFT, is a method of delivering educational or professional examinations. Competing methods include traditional linear fixed-form delivery and computerized adaptive testing. LOFT is a compromise between the two, in an effort to maintain the equivalence of the set of items that each examinee sees ...
Model-based testing moves testing to the left side of the Vs, by testing requirements, architecture, and design models. This shift begins testing almost immediately, instead of waiting a long time (traditional testing), medium time (incremental testing), or short time (Agile/DevOps) for software to become available to the right side of the Vs.
The objective of ADM is to produce standards for model-based reverse engineering of legacy systems. [4] Knowledge Discovery Metamodel (KDM) is the furthest along of these efforts, and describes information systems in terms of various assets (programs, specifications, data, test files, database schemas, etc.).
Tricentis Tosca is a software testing tool that is used to automate end-to-end testing for software applications.It is developed by Tricentis.. Tricentis Tosca combines multiple aspects of software testing (test case design, test automation, test data design and generation, and analytics) to test GUIs and APIs from a business perspective. [1]
The MDE approach is meant to increase productivity by maximizing compatibility between systems (via reuse of standardized models), simplifying the process of design (via models of recurring design patterns in the application domain), and promoting communication between individuals and teams working on the system (via a standardization of the terminology and the best practices used in the ...
ML.NET is a free software machine learning library for the C# and F# programming languages. [4] [5] [6] It also supports Python models when used together with NimbusML.The preview release of ML.NET included transforms for feature engineering like n-gram creation, and learners to handle binary classification, multi-class classification, and regression tasks. [7]