Improve Complexity Management with
Model-Based Design in V-Modell
Polarion User-Conference 2013
Stuttgart, 01.10.2013
© 2013 The MathWorks, Inc.1
The MathWorks Team Today
Michael Hopfenzitz
Senior Account Manager
Christian Guß
Application Engineer
2
Agenda

Introduction

Complexity in Embedded Software Projects

MathWorks User-Stories

Model-Based Design Approach

Traceability between Polarion Requirements and Simulink
3
MathWorks at a Glance
Earth’s topography
on a Miller cylindrical
projection, created
with MATLAB and
Mapping Toolbox
● Headquarters:
Natick, Massachusetts US
● Other U.S. Locations:
California, Michigan,
Texas, Washington, DC
● Europe:
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Netherlands, Spain, Sweden,
Switzerland, United Kingdom
● Asia-Pacific:
Australia, China, India,
Japan, Korea
● Worldwide training
and consulting
● Distributors serving more
than 20 countries
4
High-Integrity Applications
Software-based systems that are designed and maintained such that
they have a high probability of carrying out their intended function
cf. Buncefield Investigation Glossary www.buncefieldinvestigation.gov.uk/glossary.htm
5
Weinmann Develops Life-Saving Transport
Ventilator Using Model-Based Design
Challenge
Develop embedded software for an advanced emergency
and hospital transport ventilator
The MEDUMAT Transport ventilator.
Image © Weinmann Medical Technology.
Solution
Use MATLAB and Simulink for Model-Based Design to
model and simulate the controller, generate production
code, and streamline compliance certification
“Modeling, simulating, and
Results
greatly simplified compliance
 Code development and reviews accelerated
by 50%
 Dozens of design alternatives explored
 60% of core design reused
implementing the ventilator’s
embedded software with Simulink
certification. The model helped
ensure a structured development
process and provided thorough
documentation and a visual
representation of the system for the
certification review.”
Dr. Florian Dietz
Weinmann
Link to user story
6
Complexity Challenges in Software Development
RESEARCH
REQUIREMENTS
SPECIFICATIONS
Requirement Documents
• Difficult to analyze
• Difficult to manage as they change
Paper Specifications
• Easy to misinterpret
• Difficult to integrate with design
DESIGN
EDA
Algorithm
Design
MCAD/
MCAE
Electrical
Components
Embeddable
Algorithms
Mechanical
Components
IMPLEMENTATION
Physical Prototypes
• Incomplete and expensive
• Prevents rapid iteration
• No system-level testing
Manual Coding
• Time consuming
• Introduces defects and variance
• Difficult to reuse
C/C++
Embedded
Software
Testing
• Design and integration issues found late
• Difficult to feed insights back into design
process
• Traceability
INTEGRATION AND TEST
7
What is Model-Based Design?
Model, Simulate, Verify the
control algorithm,
Auto-generate C code,
Deploy & Test on the
embedded hardware
8
Example: Glycemic Control System
Input
Controller
Sensor
Plant
Output
9
Executable Specification
10
Component Design – Subsystems
11
Model-Based Design
Development Process
Requirements
User Acceptance
Testing
Complete
Integration
& Test
System Design
Environment
Integration
testing
Physical Components
Algorithms
System-Level
Integration & Test
System-Level
Specification
Code
Verification and
Validation
Component Design
Research
Subsystem
Design
Embedded
Software
Digital
Electronics
C, C++
Data Analysis
Algorithm
Development
MCU
Subsystem
Integration & Test
VHDL, Verilog
DSP
FPGA
ASIC
Integration
Data
Modeling
Implementation
Subsystem
Implementation
12
Model-Based Design
Development Process
Requirements capturing in
Polarion
Requirements
User Acceptance
Testing
Complete
Integration
& Test
System Design
Environment
Integration
testing
Physical Components
Algorithms
System-Level
Integration & Test
System-Level
Specification
Code
Verification and
Validation
Component Design
Research
Subsystem
Design
Embedded
Software
Digital
Electronics
C, C++
Data Analysis
Algorithm
Development
MCU
Subsystem
Integration & Test
VHDL, Verilog
DSP
FPGA
ASIC
Integration
Data
Modeling
Implementation
Subsystem
Implementation
13
Polarion Connector for MATLAB Simulink
See: www.polarion.com/connectors/matlab
Extension Requirements
 Polarion 2013
 MATLAB/Simulink 2013a
 Simulink Validation and Verification Toolbox
14
Highlight Requirements Inside
15
Highlight Requirements Inside
16
Traceability from Simulink to Polarion
17
Traceability from Simulink to Polarion
18
Traceability from Polarion to Simulink
Link to Simulink Model
19
Model-Based Design
Multi-Domain Modeling and Algorithm Development
Methods for modeling systems in different domains
Requirements
User Acceptance
Testing
Complete
Integration
& Test
System Design
Environment
Integration
testing
Physical Components
Algorithms
System-Level
Integration & Test
System-Level
Specification
Physical Modeling
Code
(Schematic)
Data Flow (Block diagram)
Verification and
Validation
Component Design
Research
Subsystem
Design
Modeling of
Event-Driven
Systems
(State Machines)
Implementation
Embedded
Software
Digital
Electronics
C, C++
Data Analysis
MCU
Algorithm
Development
Data
Modeling
VHDL, Verilog
DSP
FPGA
ASIC
Subsystem
Integration & Test
Programing
Language
(Textual)
Integration
Subsystem
Implementation
20
Model-Based Design
Early Concept Verification
Requirements
User Acceptance
Testing
• Executable
System
Design
System-Level
Specification
specifications
• Predict dynamic system behaviour
Environment
by simulation
Physical Components
- System & environment models
Algorithms - Less physical prototypes
• Use of simulation results for system design
- Fast What-/If studies
Component Design
- Short
iteration cycles
Research
Subsystem
Design
Embedded
Software
Digital
Electronics
C, C++
Complete
Integration
& Test
Integration
testing
System-Level
Integration & Test
Code
Verification and
Validation
Subsystem
Integration & Test
VHDL, Verilog
Data Analysis
MCU
Algorithm
Development
Data
Modeling
Idea
DSP
FPGA
ASIC
Integration
Implementation
Subsystem
Simple Model
Implementation
Detailed Model
21
Model-Based Design
Automatic Code Generation
Requirements
• C/C++, VHDL and PLC-Code Generation
User Acceptance
Testing
from one model
C, C++
System Design
MCU
• Support for Fixed Point Data Format
VHDL, Verilog
DSP
FPGA
Structured Text
PLC Complete
ASIC
Integration
& Test
Environment
• Automatic scaling
• Supported in Simulation and Code-Generation
Physical Components
Integration
testing
PLC Coder
(Structured Text)
PLC
Algorithms
• Easy integration of legacy C/C++-Code
System-Level
Integration & Test
System-Level
Specification
• System
development
Componentindependent
Design
of the target
Research
Subsystem
Design
Embedded Coder
(C, C++)
EmbeddedDSP & µC
Digital
Software
Electronics
C, C++
Data Analysis
Algorithm
Development
MCU
HDL Coder
Code (VHDL, Verilog)
Verification and
Validation
Subsystem
Integration & Test
FPGA & ASIC
VHDL, Verilog
DSP
FPGA
ASIC
Integration
Data
Modeling
Implementation
Subsystem
Implementation
22
Traceability: Requirement  Model Code
HTML Code Generation Report
23
Model-Based Design
Verification and Validation
Continuous Verification and Validation
Requirements
System Design
Environment
Physical Components
Algorithms
System-Level
Specification
Component Design
Research
Subsystem
Design
Algorithm
Development
Complete
Integration
& Test
Integration
testing
System-Level
Integration & Test
Code
Verification and
Validation
Embedded
Software
Digital
Electronics
C, C++
Data Analysis
User Acceptance
Testing
MCU
Subsystem
Integration & Test
VHDL, Verilog
DSP
FPGA
ASIC
Integration
Data
Modeling
Implementation
Subsystem
Implementation
24
Benefits of Model-Based Design
 Models:




Core of the Development Process
Unambiguous Description of Requirements
(Executable Specification)
Fast Evaluation of Design Variants
Frontloading - Early Test and Verification
Automatic Code Generation
 Better Cooperation, Communication
and Collaboration
 Higher Product Quality
Executable
Specifications
Design
with
Simulation
Models
Continuous
Test and
Verification
Automatic
Code Generation
25
Support and Community
Application Engineering
Technical Support
26