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Software Verification and Validation
Published in Richard C. Fries, Handbook of Medical Device Design, 2019
Functional tests are those where an input is supplied and the behavior of the software is compared to the expected results. This type of testing is also called “black box” testing or “behavioral” testing because the tester does not need to understand how the software works in order to develop test cases, just what it is supposed to do. These tests focus on the requirement specifications of the system. They attempt to find incorrect or missing functions, interface errors, errors in data structures or database access, and initialization and termination errors. Functional testing generally begins by creating a model of the requirement specifications and then developing test cases from the model. Some strategies that are used for functional testing include the following.
Web Application Frameworks
Published in Akshi Kumar, Web Technology, 2018
Test-driven development: Rails embraces test-driven development. Unit testing for testing individual pieces of code, functional testing for testing how individual pieces of code interact, and integration testing for testing the whole system.
Waste reduction via image classification algorithms: beyond the human eye with an AI-based vision
Published in International Journal of Production Research, 2023
Mohammad Shahin, F. Frank Chen, Ali Hosseinzadeh, Hamed Bouzary, Awni Shahin
Today's intelligent manufacturing systems currently employ IoT production, functional testing, and fault detection tools and equipment to automate defect detection to improve quality and productivity (Althubiti et al. 2022). Their investigation demonstrates how I4.0 innovations including computer-based vision can contribute to waste reduction by monitoring and detecting damaged packages before they are dispatched. For this purpose, an image classification and object recognition dataset were used, which comprised many examples of defective vs. non-defective packages that could be classified. Previously, such tasks were carried out employing the human eye directly or indirectly using cameras that feed images to a screen monitored by a human eye. Nevertheless, integrating automation and big data in I4.0 (Kelm et al. 2013) can help in computer-based vision detection systems.
Multiplane fused deposition modeling: a study of tensile strength
Published in Mechanics Based Design of Structures and Machines, 2019
Ismayuzri Bin Ishak, David Fleming, Pierre Larochelle
Three dimensional-printed parts are associated with developing prototypes for functional testing where the mechanical properties of the printed parts tend to be weaker than parts manufactured using conventional manufacturing processes (Kim et al. 2017). To make a deliverable product using a 3D printer requires an understanding of the mechanical characterization of 3D-printed materials. The printed product can be tested using available mechanical property test standards (ASTM D638–142014). In addition, ASTM International proposed a new standard to determine specific mechanical properties of materials made with additive manufacturing processes (ASTM 2013) but it is still under development. To understand factors influencing the mechanical properties of 3D-printed parts, additive manufacturing processes to fabricated 3D-printed parts need to be investigated. An example of a toolpath for printing a tensile specimen defining the key process planning parameters (perimeter, infill, raster angle, and layer height) is shown in Figure 1.