Effective redesign and preventative new design capabilities improved significantly. The comparisons between test and analysis are based on a set of metrics the more the better. These give a broader validation between model and test and also provide a richer archive of legacy data. Early program comparisons of test and analysis can help both plans and assumptions evolve. Many companies use FEA to predict test fixture strength and stiffness. In some cases, interaction between fixture and test article is inevitable and can be quantified dynamic interaction or fixture flexibility.
The positioning of the verification step can be seen in Fig.
Interestingly, Code Verification is included upstream of that. In many cases, repeating formal benchmarks of classical solutions to check the FEA Solver accuracy would be redundant. However, as we move more into multiphysics, micro mechanics and other less understood areas, it may well be that Code Verification responsibility has to move away from the FEA Vendor. Uncertainty Qualification I am not qualified to comment on Uncertainty Qualification in test, but believe it is an inexact science in FEA.
We have methods of assessing mesh convergence to give confidence in FEA local stresses, but they are ad hoc. A simple automated metric can mislead here, without an understanding of load paths and stress distribution.
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The challenge to a good understanding of why stresses occur is that it is difficult for anyone, other than an expert, to picture. This is where FEA post-processing lets us down. There is a set of tools that could be developed to allow us to understand the results in a way which is required for effective verification. A further shortfall of current FEA practice is the assessment of uncertainty over boundary conditions and loading.
Accurate modeling of these aspects can be difficult. We can carry out sensitivity studies on loading levels and line of action, boundary stiffness and others, but it is tedious to do this manually. Stages of Model Evolution The various stages of model evolution shown in Fig. The Conceptual Model is perhaps a misleading title, as it may not be a numerical model in any sense, but instead reflects the knowledge and information we have in our minds when assessing the structure to analyze and test remember the integrated approach. Questions here would include what is the type of structural configuration, design objective, loading and constraint environment.
Based on our experience, knowledge and training, we are going to make early decisions on modeling and test strategy.
Software Verification and Analysis
For a small-scale project this might come down to an informal plan for pre-analysis actions and data needed to be collected. It may even be a simple exploratory FEA model. The key here is that structural analysis is knowledge, not just data transfer. Assumptions have to be questioned and the Mathematical Model provides that catalyst.
Analysis target metrics can also be set, with ballpark comparisons against test. This could be a simple, thoroughly checked load balance diagram, with supporting calculations.
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It is based on the thinking behind the conceptual model and the implementation and results of the mathematical model. Validation Uncertainty If we are validating results between test and analysis and the range of validated designs is well populated, then we are interpolating data and would hope for good predictions.
However, if we have to move outside our comfort zone, as shown in Fig.
One cautionary note: For some work the physics, problem complexity and hypothesis describing the phenomena can change, and our usual analysis method may not be appropriate. Conversely, an aircraft structure analysis may not be required to demonstrate failure, but to show stresses within the elastic limit.
If this level is exceeded, then a redesign is required as the limit load is established from extensive testing. This is an analysis exercise rather than a full simulation exercise. Prediction and confirmation of the physics appear in Verification and Validation respectively. The ASME process plan is a great start. Alpha testing is often employed for off-the-shelf software as a form of internal acceptance testing before the software goes to beta testing.
Beta testing comes after alpha testing and can be considered a form of external user acceptance testing. Versions of the software, known as beta versions , are released to a limited audience outside of the programming team known as beta testers. The software is released to groups of people so that further testing can ensure the product has few faults or bugs. Beta versions can be made available to the open public to increase the feedback field to a maximal number of future users and to deliver value earlier, for an extended or even indefinite period of time perpetual beta.
Software Verification and Analysis: An Integrated, Hands-On Approach / Edition 1
Functional testing refers to activities that verify a specific action or function of the code. These are usually found in the code requirements documentation, although some development methodologies work from use cases or user stories. Functional tests tend to answer the question of "can the user do this" or "does this particular feature work.
Non-functional testing refers to aspects of the software that may not be related to a specific function or user action, such as scalability or other performance , behavior under certain constraints , or security. Testing will determine the breaking point, the point at which extremes of scalability or performance leads to unstable execution.
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Non-functional requirements tend to be those that reflect the quality of the product, particularly in the context of the suitability perspective of its users. Continuous testing is the process of executing automated tests as part of the software delivery pipeline to obtain immediate feedback on the business risks associated with a software release candidate. Destructive testing attempts to cause the software or a sub-system to fail. It verifies that the software functions properly even when it receives invalid or unexpected inputs, thereby establishing the robustness of input validation and error-management routines.
Various commercial non-functional testing tools are linked from the software fault injection page; there are also numerous open-source and free software tools available that perform destructive testing. Performance testing is generally executed to determine how a system or sub-system performs in terms of responsiveness and stability under a particular workload.
It can also serve to investigate, measure, validate or verify other quality attributes of the system, such as scalability, reliability and resource usage. Load testing is primarily concerned with testing that the system can continue to operate under a specific load, whether that be large quantities of data or a large number of users. This is generally referred to as software scalability.
The related load testing activity of when performed as a non-functional activity is often referred to as endurance testing. Volume testing is a way to test software functions even when certain components for example a file or database increase radically in size. Stress testing is a way to test reliability under unexpected or rare workloads. Stability testing often referred to as load or endurance testing checks to see if the software can continuously function well in or above an acceptable period.
There is little agreement on what the specific goals of performance testing are.
The terms load testing, performance testing, scalability testing , and volume testing, are often used interchangeably. Real-time software systems have strict timing constraints. To test if timing constraints are met, real-time testing is used. Usability testing is to check if the user interface is easy to use and understand. It is concerned mainly with the use of the application. This is not a kind of testing that can be automated; actual human users are needed, being monitored by skilled UI designers. Accessibility testing may include compliance with standards such as:.
Security testing is essential for software that processes confidential data to prevent system intrusion by hackers. The International Organization for Standardization ISO defines this as a "type of testing conducted to evaluate the degree to which a test item, and associated data and information, are protected so that unauthorised persons or systems cannot use, read or modify them, and authorized persons or systems are not denied access to them.
Testing for internationalization and localization validates that the software can be used with different languages and geographic regions. The process of pseudolocalization is used to test the ability of an application to be translated to another language, and make it easier to identify when the localization process may introduce new bugs into the product.
Globalization testing verifies that the software is adapted for a new culture such as different currencies or time zones. Actual translation to human languages must be tested, too. Possible localization and globalization failures include:.
Verification and Validation Activities - Emenda
Development Testing is a software development process that involves the synchronized application of a broad spectrum of defect prevention and detection strategies in order to reduce software development risks, time, and costs. It is performed by the software developer or engineer during the construction phase of the software development lifecycle. Development Testing aims to eliminate construction errors before code is promoted to other testing; this strategy is intended to increase the quality of the resulting software as well as the efficiency of the overall development process.
Depending on the organization's expectations for software development, Development Testing might include static code analysis , data flow analysis, metrics analysis, peer code reviews, unit testing, code coverage analysis, traceability , and other software testing practices.