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| ( 01 Jan 2010 ) |
| By Brett Murphy, The MathWorks |
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Virtual testing, based on system simulation and Model-Based Design, takes the traditional “test-at-the-end” system development process (represented in the V diagram) and makes it more iterative. Virtual testing shortens both the design cycle and the final physical testing phase.
The problems Complexity in embedded software development is driving the cost of test and verification to as much as 70 percent of overall development costs. Industrial automation, automotive, and aerospace engineers conduct exhaustive design and code reviews and build increasingly complex test systems to confirm that the software in embedded processors meets high-integrity standards and design requirements. And as verification consumes more time, engineers have fewer opportunities to innovate and create product differentiation through design optimization.
Many organizations are finding that most errors they uncover in test and integration were introduced at the beginning of the design process while interpreting system requirements. Engineers now face the challenge of checking for errors and "cleaning them out" closer to the beginning of the development process, when they are cheaper to fix.
Finally, as development teams grow and become geographically dispersed, they are seeking better ways to collaborate.
The solution: test early Embedded software errors can be cut substantially by doing more complete design verification at or near the beginning of the design process via systematic system simulation, or virtual testing. “Virtual” in this case denotes simulation, but with no hardware involved—just software and simulation engines. “Systematic” means building tests based on requirements and then executing those tests against the system design.
There are two critical concepts that drive virtual testing process improvements: an executable system specification and requirements based tests.
The executable system specification is a model that you can simulate, and includes your system design as well as environment models: models of the important elements of the physical world your embedded system interacts with. The system model needs to include subsystem domains such as controls, mechanical components, electrical components, and hydraulics. These models should be as detailed as needed to capture their system-level functional behavior.
Requirements-based tests are formulated from functional requirements that can be expressed as tests; essentially, "Given a particular input, here is the output I expect." At a minimum, you need to have a simulation input signal or sequence for each test, as well as output captured from the simulation, to compare with the expected output. You should also build a complete set of tests that fully exercise the requirements.
Model-based design As embedded software grows in functionality and complexity, engineering teams are moving beyond traditional code development techniques of using text editors and debuggers. They’re shifting to design centered on models, using modeling, simulation, and code generation tools on the desktop. This model-centric development approach is called Model-Based Design.
Using models and simulation at the core of the development process provides insight into the dynamics and algorithmic aspects of the system. In addition, the models can be used to: create executable specifications; communicate system (and subsystem) requirements and interface definitions; provide virtual prototypes or models of the complete system; and automatically generate code for embedded software algorithms or logic.
Embedded system developers in industrial control, automotive, and aerospace are adopting Model-Based Design to improve their development processes and manage costs, while maintaining quality. They use models and simulation to increase efficiency with complex system designs, and automatic code generation from models to streamline implementation.
Designing with models While simulation alone will not find all errors, it is a huge step forward and can be done almost as soon as you design a model. Iterating in a modeling environment is fast and easy. A whole system model allows the development group to check if the design is going to work, if requirements make sense, and if the design meets those requirements.
Modeling individual components is incredibly useful and may be necessary to complete a complex design, but it’s helpful to first model the system or environment your component will operate in. By modeling the whole system in a single environment, you can quickly see how the functionality of your component will interact with other components and how the integrated components will behave in the deployed system or environment. You can also find missing requirements for your individual component or others. With a system model to return to as you iterate one component, you can assess how design iterations will affect system functionality.
Testing models Developing tests in parallel to the design process enables early detection of potential problems and significantly reduces the cost and time for fixing them. By thinking about testing while developing the model, you can design better for "testability," thereby ensuring the design can be fully tested.
Conclusion One of the primary benefits of Model-Based Design is the opportunity to conduct verification and validation in parallel with all other development steps, especially early in the development process. Developing tests along with models, and reusing model tests on code and hardware, significantly reduces the risk of uncovering errors late in the process and jeopardizing quality or delivery goals.
Anticipating the upturn following the current recession, engineering teams are looking for ways to seize advantage over rivals by reducing the cost of test and verification, while strengthening their ability to develop innovative products faster. These seemingly contradictory goals can be achieved through early verification with Model-Based Design. Early verification starts with an executable system specification and requirements based tests that can be used for virtual testing, prior to design partitioning and component implementation. This approach allows engineers to verify designs well before final system integration and test, and resolve errors when they have less effect on cost and schedule.
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