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Traditionally, embedded software algorithms were manually documented. The process was not only , but also took months to complete. With rapid advancements in embedded systems, the complexity and code size of their software has amplified. Developing applications for different systems in a connected vehicle, for instance, could involve writing , which can take years to perfect. The pressures of new technology integration and safety compliance requirements add to these challenges and often end up impacting project timeframes and costs. Considering that in 2017, engineers are exploring alternatives that ensure their successful completion. Recent trends show a paradigm shift towards a model-based approach to embedded software development.

Towards Leaner, Faster Models

As , more instances of mismatched assumptions between the embedded hardware and software come to the fore, raising quality concerns. Model-based engineering can redress the risk and help developers ensure performance, time criticality, reliability, and safety. Packages such as MATLAB have the potential to model, simulate, automatically generate code, and test software algorithms while maintaining control over the revisions and versions. . It even allowed virtual simulation and verification of control algorithms, eliminating possibilities of equipment damage during hardware-software integration.

Reliability Prediction for Fool-Proof Design

While building safety-critical systems, it is essential to ensure software design reliability at an early stage. With , predicting the application’s reliability before a line of code is generated can help monitor and control the final product. An (ESRPM) can take this a step further by quantifying the quality of the developed software with 90 percent accuracy. The idea is to base the ESRPM model on the embedded software’s requirement specification. Leveraging these details, a . The approach can explain any future problem, and minimize wastage and rework efforts. The resultant software is robust, dependable, and devoid of cascading disasters. The next stage of developing reliable embedded software will be ushered in by an Ada-based language called SPARK. With safety and reliability at its core, the language aims at increasing developers’ productivity, integrating scientific computations, and enriching dynamic capabilities. While still a nascent concept, it promises to revolutionize the embedded software development space.

Enabling Real-Time Capabilities

ISO certification is integral to safety-critical embedded software. For manufacturers of such embedded devices, ISO certification involves assessing the performance of the program in variable environments and validating real-time reliability. Since mathematical models fail to predict real-time reliability responses, a combination of the model-based technique and formal analysis tools can reduce costs while improving consistency. Tools like . Its ability to generate production codes automatically enables enterprises to achieve DO-178B and C compliance certification for flight control systems of unmanned aerial vehicles.

Unleashing Multi-Processing Power

Adopting multicore technology, like heterogeneous multiple-processing system-on-chip (MPSoC) can extend software capabilities and increase energy efficiency and performance at low costs. On the other hand, processing units such as Zynq UltraScale+MPSoC can provide a programming methodology to design and develop IoT and real-time enabled applications. These while complying to ISO 26262 and AUTOSAR standards.

Accelerating Product Enhancements

For modern organizations focusing on delivery, the goal is to automate tests using a continuous integration and delivery platform. The model-based tool can enable engineers to develop plugins, detect faults, debug, manage pipelines and evaluate performance while controlling versions and upgrades. A leading automotive component supplier .

A Smarter Future

The next few years will see enabling embedded software to reduce its reliance on hardware. Though embedded system developers primarily use platform-dependent environments, parts of software development, like firmware programming and debugging are already hardware agnostic. Performance testing to assess plant behavior is often simulated using a mock embedded hardware interface. With the , the future is green for applications embedded in multi-processors. The technology will support further advancements, like and embedded machine vision technology. Progress in that can support embedded operating systems and processors will help realize the embedded vision dream with smarter image sensors.