Verifying Code to Be Safe and Secure with Static Analysis in Polyspace
With growing complexity in embedded software, software testing and reviews are getting more time-consuming and challenging than ever before, particularly for high-integrity applications. Software testing can only show the presence, but never the absence of errors. Formal methods-based static analysis can exhaustively prove the absence of certain run-time errors and properties of generated or handwritten C and C++ code.
This demo shows how to apply Polyspace® static analysis to:
- Comply with MISRA® coding guidelines
- Achieve credits to IEC 61508, ISO 26262, IEC 62304, and DO-178 requirements
- Uncover security vulnerabilities according to CERT-C and ISO 17961
- Fix programming defects as soon as they are introduced
Technology Focus: Static code analysis
Key Products: Polyspace Bug Finder™, Polyspace Code Prover™, IEC Certification Kit, DO Qualification Kit
New for 2017: Automated Driving System Toolbox and Powertrain Blockset
Automated Driving System Toolbox™ provides algorithms, tools, and applications to support the design and testing of assisted and automated driving systems. Powertrain Blockset™ provides fully assembled reference application models of automotive powertrains, including gasoline, diesel, hybrid, and electric systems.
Come and see how they can help with:
- Automatic detection and tracking using image and video processing
- Performing sensor fusion and object tracking
- Visualising and validating of results
- Performing drive-cycle simulations with a vehicle or dynamometer model
- Carrying out trade-off analysis and component sizing, control parameter optimization, and hardware-in-the-loop testing
Technology Focus: Sensor fusion and visualisation, powertrain simulation
Key Products: Automated Driving System Toolbox, Powertrain Blockset
Predictive Maintenance with MATLAB and Simulink
Predictive maintenance is the intelligent health monitoring of equipment to avoid future failure. In contrast to preventive maintenance, which follows a set timeline, predictive maintenance schedules are determined by analytic algorithms and data from equipment sensors, saving resources and increasing uptime of assets.
Visit this showcase to understand how you can use MATLAB® and Simulink ® to easily develop predictive maintenance algorithms. This demo will cover:
- Processing data from sensors
- Using physical modelling to generate failure data
- Building machine learning algorithms to predict when components will fail
- Deploying predictive maintenance algorithms into enterprise IT and embedded hardware
Technology Focus: Machine learning, signal processing, physical modelling
Key Products: Statistics and Machine Learning Toolbox™, Simscape™
Using MATLAB and ThingSpeak to Explore the Internet of Things
The adoption of Internet of Things (IoT) technologies continues to proliferate. Use of IoT spans various applications such as monitoring environmental data, health monitoring, control of household appliances, and projects in the maker movement.
This demo illustrates how MATLAB, Simulink, and ThingSpeak™ support developing and deploying IoT systems, including:
- Acquiring real-time data from sensors, including those on mobile phones using MATLAB Mobile™
- Performing analysis on your data
- Accessing and visualising the results in ThingSpeak
- Deploying algorithms created in MATLAB and Simulink directly to hardware using code generation
Technology Focus: Internet of Things, data analysis, visualisation, embedded devices
Key Products: MATLAB Coder™, Simulink Coder™, ThingSpeak, MATLAB Online™
Building, Visualising, and Deploying Physical Models
Plant models are critical to a good system design. They enable you to predict and assess the performance of your systems before even building a prototype. Come and discover the technologies you can use to build and extend multidomain (mechanical, electrical, and hydraulic) models.
Learn how to leverage your models and MathWorks tools to quickly effect sensitivity analysis, parameter tuning, and design optimization.
Technology Focus: Multidomain simulation, design optimization
Key Products: Simulink, Simscape, Simulink Design Optimization™
Model Verification and Validation in Simulink
Model-based verification and validation can accelerate the software development process while meeting the requirements for safety or industry standards. Many techniques can be automated to improve quality and ensure a design has been rigorously tested, such as:
- Proving properties of models
- Applying modelling standards
- Measuring coverage levels from tests
- Showing traceability of requirements, model, and code
Come to this demo and find out how these techniques can be easily applied to any project, not only ones with safety requirements.
Technology Focus: Verification and validation methods for models
Key Products: Simulink Verification and Validation™, Simulink Design Verifier™, Simulink Code Inspector™
5G Communications System Design in MATLAB
5G wireless technology will enable gigabit data rates, improved coverage, low latency, and increased connectivity to machines and vehicles. Hybrid RF/digital beamforming architectures with massive antenna arrays and innovative coding and modulation schemes are being considered as possible technologies to achieve this.
This demo station will showcase how these systems can be designed in MATLAB, simulated using 3D channel models, and prototyped on FPGAs using software-defined radio (SDR) platforms.
Technology Focus: 5G, RF architectures, wireless channel modelling, antenna and antenna array design, software defined radio
Key Products: 5G Library, LTE System Toolbox™, RF Toolbox™, RF Blockset™, Antenna Toolbox™, Phased Array System Toolbox™, HDL Coder™
Deploying Video Processing Algorithms to Hardware
The transition from algorithm development towards implementation is critical in the product lifecycle. With video processing algorithms needing to cross multiple hardware platforms, the ability to target a variety of platforms from a single development environment enables you to accelerate this transition while enhancing performance and quality.
Discover how you can prototype video processing algorithms developed in MATLAB and Simulink on hardware platforms, accelerating design and testing workflows.
Technology focus: Code generation, computer vision, video processing
Key products: Embedded Coder®, HDL Coder
Big Data with MATLAB
The amount of data generated by companies is ever-increasing, and while this data represents an opportunity to gain greater insight and make more informed decisions, it also presents a number of challenges. How do you handle data sets that are too big to fit in memory, too big to process on a desktop computer? There is no one-size-fits-all approach.
Visit this showcase to discover the different tools that MATLAB provides to tackle these challenges and work to deliver insights from data sets of all sizes.
Technology Focus: Big data, data analytics
Key Products: Parallel Computing Toolbox™, MATLAB Distributed Computing Server™
Deep Learning with MATLAB
Machine learning allows us to build complex models by ‘teaching’ a computer to find patterns in data. These techniques are already used to make decisions that affect all of us, from internet search and speech recognition to predictive maintenance, interpreting medical scans, and automated driving. Deep learning with neural networks has been key to this rise, enabling machines to learn increasingly complicated models, with huge improvements in accuracy.
Come and see how MATLAB can help with:
- Managing large volumes of training data
- Extracting features from data
- Training deep learning models
- Evaluating model quality
Technology Focus: Deep learning, machine learning, neural networks
Key Products: MATLAB, Statistics and Machine Learning Toolbox, Neural Network Toolbox™