SlideShare a Scribd company logo
1 of 25
A Case Study
of the Automotive Industry
Submitted To: Submitted By:
Mr. Bhupendra Gehlot GajendraMeena
(K10945)
Introduction
 Today car manufacturers produce large no. of Customized
Cars to meet customer demands & to support after market
services.
 But it is impossible to anticipate all configuration at
design time.
 Therefore they focus their attention to “Software Product
Line Method” rather than production line method.
Software Production Line Method
 Focus on the methods & tools required to create similar
product based on a collection of software assets.
 Objectives:
 Increase the ability to re use software
 To meet customization requirements
 Vital Aspect:
“Variability Management”
The combination of assets to form a single, possibly, unique
product
 Variant Handling:
Ability to modify a system without making a big impact on
the system or imposing a need to restructure the design.
Eg:
Inside Lighting System depend on the installed doors
in the car.
 Variability:
Is defined in the architecture through variation points, or a
specific place in the architecture at which a feature can
take one of two or more shapes.
 Variability Sources:
 In Function
 In Data
 In Technology
 In Control Flow
 In Environment
 In Quality
4 Variation Patterns
Pattern E.g. of Mechanism Binding Time Usage
Product
Architecture
Derivation
Configuration
management,
Generators
Pre-build Implementation during
the architecture &
design phase
Compilation Compiler Switches Pre-build Compiler flags will
resolve to one binary
output
Linking Binary Replacement Pre-build Linkage with library/
binaries to produce
one binary output
Runtime Adoption during start up
condition on variable
Post-build Uses inline code to
resolve variability at
runtime.
AUTOmotive Open System
ARchitecture (AUTOSAR)
 An open & standardized architecture for the automotive
industry.
 Jointly developed by the largest companies within the
industry together with 3rd party suppliers & tool
developers.
 Aim to improve the way electronic equipment is
developed, increase safety, performance & environmental
friendliness.
 Modules introduce in the standard
 UML Meta Models
 Annotated Meta Model
 Extended Meta Model
 4 patterns describe in the standard,
 Aggregation Value Standard
 Association Value Standard
 Attribute Value Standard
 Property Set Value Standard
What is a Quality Tree??
 Way of assessing & categorizing variant patterns used in
an organization.
 Leaf nodes represent strength &weaknesses discovered
during the implementation.
 Provide,
 Guidance for the architect when making decisions for how
to manage variability.
 Good overview of the characteristics of one specific
pattern.
Mainly Focus
Focus on key elements required to
support run time variability using the
AUTOSAR 4 .0 Standard through
developing a prototype.
Research Method
There are 3 subsections,
 Case setting
 Data source.
 Process
Case Setting
 Problem based on the Volvo Car’s preconceptions for
managing variability to implement a variant mechanisms
for run – time variability.
 There are three stages in development that variants are
used today at Volvo Cars. They are,
 compilation mechanisms
 local parameterization
 distributed parameterization.
Data Sources
Sources Type Advantages Limitations
Volvo cars
component
specification
Document, architecture
specification
Valuable information
based on refined
domain knowledge.
Restricted by
confidentiality
agreement.
Volvo cars
run-time
variability
specification
Document
,architecture
specification
Valuable information
based on refined
domain knowledge.
Draft document,
may change.
Restructured by
confidentiality
agreement.
Software
architect at
Volvo cars
Regular discussions 10 year of hand- on
architect experience
at Volvo cars
Data is
interpreted twice.
AUTOSAR
4.0
specification
Documents and UML
meta-models
Publicly available.
Thorough and with
examples.
Difficult to
address all
relevant sections.
Primary
Sources
Secondary
Sources
Process
Under this step we can divided the implementation into
three phases.
 C Implementation - Written entirely in C
 CAN-bus Implementation - Written entirely in C
 AUTOSAR Implementation - Developed using
AUTOSAR complaint tools.
To assess the specification provided by Volvo cars.
 First phase-:
Intentionally avoided any use of “AUTOSAR”. Consequently this made it possible
to discover what was required of the variant before making the prototype more true
to the automotive environment.
 Second phase-:
Findings from the first phase were used to further refine the implementation towards
the automotive industry.
 Third phase-:
Based on the findings with some limitations from the previous phases.
The company started the development based on the following premises and
requirements.
 As much as possible takes place run-time.
 A solution must be independent from the data it is supposed to pass.
 Data used by a services does not have to be stored on the ECU where the service running.
Research Data
 The results outlined in this slides are coming from a
prototype implementation of a run – time variability
pattern.
 Publisher-subscriber which is a mechanism for
components, during application execution, to subscribe to
state updates generated by another component, the so
called publisher.
 Volvo Cars' specification in its current state does not
require subscription to take place in run-time.
Implementation
Phases
Phase 1: C Implementation
Phase 2: CAN-bus Implementation
Phase 3: AUTOSAR Implementation
Quality Scenarios learnt during
Implementation
 Highlighted aspects derived during the
development:
 Subscription
 Multiple Publishers
 Push & Pull Strategies
 Register Parameters of Interest
 Local & Global configuration files
 Parameters in an AUTOSAR environment
Analysis
 Quality Tree
Automotive Industry
 Following factors have introduced for the motivation of
variability in AUTOSAR.
 Establish a common language to enable suppliers and
manufactures to work together.
 Use to avoid redundancy between artifacts.
 It provides a basis for basic software product line.
K10945 opc gajendra meena

More Related Content

Viewers also liked

2016_S_LAA6654_Quintanilla_V_BlurbSubmissionPDF_OZER
2016_S_LAA6654_Quintanilla_V_BlurbSubmissionPDF_OZER2016_S_LAA6654_Quintanilla_V_BlurbSubmissionPDF_OZER
2016_S_LAA6654_Quintanilla_V_BlurbSubmissionPDF_OZER
Valeria Quintanilla Florián
 
Pontificia universidad católica del ecuador sede ambato
Pontificia universidad católica del ecuador sede ambatoPontificia universidad católica del ecuador sede ambato
Pontificia universidad católica del ecuador sede ambato
Calfra
 
GST – An End-to-end Architecture for Automotive Telematics Services - Peter V...
GST – An End-to-end Architecture for Automotive Telematics Services - Peter V...GST – An End-to-end Architecture for Automotive Telematics Services - Peter V...
GST – An End-to-end Architecture for Automotive Telematics Services - Peter V...
mfrancis
 
FASTR_Overview2017
FASTR_Overview2017FASTR_Overview2017
FASTR_Overview2017
Craig Hurst
 

Viewers also liked (20)

Gerencia de proyectos mapa
Gerencia de proyectos mapaGerencia de proyectos mapa
Gerencia de proyectos mapa
 
Mandala de relaciones laborales
Mandala de relaciones laboralesMandala de relaciones laborales
Mandala de relaciones laborales
 
2016_S_LAA6654_Quintanilla_V_BlurbSubmissionPDF_OZER
2016_S_LAA6654_Quintanilla_V_BlurbSubmissionPDF_OZER2016_S_LAA6654_Quintanilla_V_BlurbSubmissionPDF_OZER
2016_S_LAA6654_Quintanilla_V_BlurbSubmissionPDF_OZER
 
Diagrama
DiagramaDiagrama
Diagrama
 
Ppt jude
Ppt judePpt jude
Ppt jude
 
Pontificia universidad católica del ecuador sede ambato
Pontificia universidad católica del ecuador sede ambatoPontificia universidad católica del ecuador sede ambato
Pontificia universidad católica del ecuador sede ambato
 
Programación neurolinguistica
Programación neurolinguisticaProgramación neurolinguistica
Programación neurolinguistica
 
Presentación I Jornadas Tecnicas ASET
Presentación I Jornadas Tecnicas ASETPresentación I Jornadas Tecnicas ASET
Presentación I Jornadas Tecnicas ASET
 
Giới thiệu Overview về AngularJS, Yeoman
Giới thiệu Overview về AngularJS, YeomanGiới thiệu Overview về AngularJS, Yeoman
Giới thiệu Overview về AngularJS, Yeoman
 
EVOLUCIÓN BIOLÓGICA
EVOLUCIÓN BIOLÓGICAEVOLUCIÓN BIOLÓGICA
EVOLUCIÓN BIOLÓGICA
 
MAPA ESTRATÉGICO
MAPA ESTRATÉGICOMAPA ESTRATÉGICO
MAPA ESTRATÉGICO
 
Sewells MSXI ADCI Report Oct-Dec 2016 Edition
Sewells MSXI ADCI Report Oct-Dec 2016 EditionSewells MSXI ADCI Report Oct-Dec 2016 Edition
Sewells MSXI ADCI Report Oct-Dec 2016 Edition
 
GST – An End-to-end Architecture for Automotive Telematics Services - Peter V...
GST – An End-to-end Architecture for Automotive Telematics Services - Peter V...GST – An End-to-end Architecture for Automotive Telematics Services - Peter V...
GST – An End-to-end Architecture for Automotive Telematics Services - Peter V...
 
Técnicas de habilidades gerenciales
Técnicas de habilidades gerencialesTécnicas de habilidades gerenciales
Técnicas de habilidades gerenciales
 
Service Oriented Architecture In Automotive
Service Oriented Architecture In AutomotiveService Oriented Architecture In Automotive
Service Oriented Architecture In Automotive
 
Evolución de la Gestión del Talento humano
Evolución de la Gestión del Talento humano Evolución de la Gestión del Talento humano
Evolución de la Gestión del Talento humano
 
Automotive architecture examples with EAST-ADL models
Automotive architecture examples with EAST-ADL modelsAutomotive architecture examples with EAST-ADL models
Automotive architecture examples with EAST-ADL models
 
Radiografía de un entrevistador
Radiografía de un entrevistadorRadiografía de un entrevistador
Radiografía de un entrevistador
 
FASTR_Overview2017
FASTR_Overview2017FASTR_Overview2017
FASTR_Overview2017
 
Software enginnering
Software enginneringSoftware enginnering
Software enginnering
 

Similar to K10945 opc gajendra meena

Case study analysis of automotive industry.
Case study analysis of automotive industry.Case study analysis of automotive industry.
Case study analysis of automotive industry.
Rashmi Dissanayake
 
Ajay_Training_Report[1]
Ajay_Training_Report[1]Ajay_Training_Report[1]
Ajay_Training_Report[1]
AJAY KUMAR
 
1) Question Add Targets to Balanced score Card
1) Question  Add Targets to Balanced score Card1) Question  Add Targets to Balanced score Card
1) Question Add Targets to Balanced score Card
MartineMccracken314
 
1) Question Add Targets to Balanced score Card
1) Question  Add Targets to Balanced score Card1) Question  Add Targets to Balanced score Card
1) Question Add Targets to Balanced score Card
AbbyWhyte974
 
INDUSTRIAL TRAINING REPORT
INDUSTRIAL TRAINING REPORTINDUSTRIAL TRAINING REPORT
INDUSTRIAL TRAINING REPORT
SUYASH TRIVEDI
 
Automation Framework Design
Automation Framework DesignAutomation Framework Design
Automation Framework Design
Kunal Saxena
 

Similar to K10945 opc gajendra meena (20)

Case study analysis of automotive industry.
Case study analysis of automotive industry.Case study analysis of automotive industry.
Case study analysis of automotive industry.
 
BX-D – A Business Component & XML Driven Test Automation Framework
BX-D – A Business Component & XML Driven Test Automation FrameworkBX-D – A Business Component & XML Driven Test Automation Framework
BX-D – A Business Component & XML Driven Test Automation Framework
 
Car Recommendation System Using Customer Reviews
Car Recommendation System Using Customer ReviewsCar Recommendation System Using Customer Reviews
Car Recommendation System Using Customer Reviews
 
Virtual Commissioning of Small to Medium Scale Industry Using the Concepts of...
Virtual Commissioning of Small to Medium Scale Industry Using the Concepts of...Virtual Commissioning of Small to Medium Scale Industry Using the Concepts of...
Virtual Commissioning of Small to Medium Scale Industry Using the Concepts of...
 
Vave two wheelers
Vave two wheelersVave two wheelers
Vave two wheelers
 
CMAPS_KPIT_Siddharth Mishra.pptx
CMAPS_KPIT_Siddharth Mishra.pptxCMAPS_KPIT_Siddharth Mishra.pptx
CMAPS_KPIT_Siddharth Mishra.pptx
 
Ajay_Training_Report[1]
Ajay_Training_Report[1]Ajay_Training_Report[1]
Ajay_Training_Report[1]
 
Sdpl1
Sdpl1Sdpl1
Sdpl1
 
Predicting Machine Learning Pipeline Runtimes in the Context of Automated Mac...
Predicting Machine Learning Pipeline Runtimes in the Context of Automated Mac...Predicting Machine Learning Pipeline Runtimes in the Context of Automated Mac...
Predicting Machine Learning Pipeline Runtimes in the Context of Automated Mac...
 
1) Question Add Targets to Balanced score Card
1) Question  Add Targets to Balanced score Card1) Question  Add Targets to Balanced score Card
1) Question Add Targets to Balanced score Card
 
1) Question Add Targets to Balanced score Card
1) Question  Add Targets to Balanced score Card1) Question  Add Targets to Balanced score Card
1) Question Add Targets to Balanced score Card
 
1) question add targets to balanced score card
1) question  add targets to balanced score card1) question  add targets to balanced score card
1) question add targets to balanced score card
 
INDUSTRIAL TRAINING REPORT
INDUSTRIAL TRAINING REPORTINDUSTRIAL TRAINING REPORT
INDUSTRIAL TRAINING REPORT
 
A CASE Lab Report - Project File on "ATM - Banking System"
A CASE Lab Report - Project File on  "ATM - Banking System"A CASE Lab Report - Project File on  "ATM - Banking System"
A CASE Lab Report - Project File on "ATM - Banking System"
 
virtual-system-integration-and-early-functional-validation-in-the-whole-vehic...
virtual-system-integration-and-early-functional-validation-in-the-whole-vehic...virtual-system-integration-and-early-functional-validation-in-the-whole-vehic...
virtual-system-integration-and-early-functional-validation-in-the-whole-vehic...
 
Automation Framework Design
Automation Framework DesignAutomation Framework Design
Automation Framework Design
 
Powertrain Component Modelling and Sizing.pdf
Powertrain Component Modelling and Sizing.pdfPowertrain Component Modelling and Sizing.pdf
Powertrain Component Modelling and Sizing.pdf
 
A Review of Feature Model Position in the Software Product Line and Its Extra...
A Review of Feature Model Position in the Software Product Line and Its Extra...A Review of Feature Model Position in the Software Product Line and Its Extra...
A Review of Feature Model Position in the Software Product Line and Its Extra...
 
Project synopsis.
Project synopsis.Project synopsis.
Project synopsis.
 
Simplify 3X
Simplify 3XSimplify 3X
Simplify 3X
 

Recently uploaded

Spellings Wk 4 and Wk 5 for Grade 4 at CAPS
Spellings Wk 4 and Wk 5 for Grade 4 at CAPSSpellings Wk 4 and Wk 5 for Grade 4 at CAPS
Spellings Wk 4 and Wk 5 for Grade 4 at CAPS
AnaAcapella
 

Recently uploaded (20)

NO1 Top Black Magic Specialist In Lahore Black magic In Pakistan Kala Ilam Ex...
NO1 Top Black Magic Specialist In Lahore Black magic In Pakistan Kala Ilam Ex...NO1 Top Black Magic Specialist In Lahore Black magic In Pakistan Kala Ilam Ex...
NO1 Top Black Magic Specialist In Lahore Black magic In Pakistan Kala Ilam Ex...
 
How to Manage Call for Tendor in Odoo 17
How to Manage Call for Tendor in Odoo 17How to Manage Call for Tendor in Odoo 17
How to Manage Call for Tendor in Odoo 17
 
Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)
 
dusjagr & nano talk on open tools for agriculture research and learning
dusjagr & nano talk on open tools for agriculture research and learningdusjagr & nano talk on open tools for agriculture research and learning
dusjagr & nano talk on open tools for agriculture research and learning
 
FICTIONAL SALESMAN/SALESMAN SNSW 2024.pdf
FICTIONAL SALESMAN/SALESMAN SNSW 2024.pdfFICTIONAL SALESMAN/SALESMAN SNSW 2024.pdf
FICTIONAL SALESMAN/SALESMAN SNSW 2024.pdf
 
REMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptxREMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptx
 
On_Translating_a_Tamil_Poem_by_A_K_Ramanujan.pptx
On_Translating_a_Tamil_Poem_by_A_K_Ramanujan.pptxOn_Translating_a_Tamil_Poem_by_A_K_Ramanujan.pptx
On_Translating_a_Tamil_Poem_by_A_K_Ramanujan.pptx
 
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptxHMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
 
Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024
 
AIM of Education-Teachers Training-2024.ppt
AIM of Education-Teachers Training-2024.pptAIM of Education-Teachers Training-2024.ppt
AIM of Education-Teachers Training-2024.ppt
 
Wellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptxWellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptx
 
Spellings Wk 4 and Wk 5 for Grade 4 at CAPS
Spellings Wk 4 and Wk 5 for Grade 4 at CAPSSpellings Wk 4 and Wk 5 for Grade 4 at CAPS
Spellings Wk 4 and Wk 5 for Grade 4 at CAPS
 
OSCM Unit 2_Operations Processes & Systems
OSCM Unit 2_Operations Processes & SystemsOSCM Unit 2_Operations Processes & Systems
OSCM Unit 2_Operations Processes & Systems
 
Tatlong Kwento ni Lola basyang-1.pdf arts
Tatlong Kwento ni Lola basyang-1.pdf artsTatlong Kwento ni Lola basyang-1.pdf arts
Tatlong Kwento ni Lola basyang-1.pdf arts
 
21st_Century_Skills_Framework_Final_Presentation_2.pptx
21st_Century_Skills_Framework_Final_Presentation_2.pptx21st_Century_Skills_Framework_Final_Presentation_2.pptx
21st_Century_Skills_Framework_Final_Presentation_2.pptx
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentation
 
Exploring_the_Narrative_Style_of_Amitav_Ghoshs_Gun_Island.pptx
Exploring_the_Narrative_Style_of_Amitav_Ghoshs_Gun_Island.pptxExploring_the_Narrative_Style_of_Amitav_Ghoshs_Gun_Island.pptx
Exploring_the_Narrative_Style_of_Amitav_Ghoshs_Gun_Island.pptx
 
latest AZ-104 Exam Questions and Answers
latest AZ-104 Exam Questions and Answerslatest AZ-104 Exam Questions and Answers
latest AZ-104 Exam Questions and Answers
 
COMMUNICATING NEGATIVE NEWS - APPROACHES .pptx
COMMUNICATING NEGATIVE NEWS - APPROACHES .pptxCOMMUNICATING NEGATIVE NEWS - APPROACHES .pptx
COMMUNICATING NEGATIVE NEWS - APPROACHES .pptx
 
Simple, Complex, and Compound Sentences Exercises.pdf
Simple, Complex, and Compound Sentences Exercises.pdfSimple, Complex, and Compound Sentences Exercises.pdf
Simple, Complex, and Compound Sentences Exercises.pdf
 

K10945 opc gajendra meena

  • 1. A Case Study of the Automotive Industry Submitted To: Submitted By: Mr. Bhupendra Gehlot GajendraMeena (K10945)
  • 2. Introduction  Today car manufacturers produce large no. of Customized Cars to meet customer demands & to support after market services.  But it is impossible to anticipate all configuration at design time.  Therefore they focus their attention to “Software Product Line Method” rather than production line method.
  • 3. Software Production Line Method  Focus on the methods & tools required to create similar product based on a collection of software assets.  Objectives:  Increase the ability to re use software  To meet customization requirements  Vital Aspect: “Variability Management” The combination of assets to form a single, possibly, unique product
  • 4.  Variant Handling: Ability to modify a system without making a big impact on the system or imposing a need to restructure the design. Eg: Inside Lighting System depend on the installed doors in the car.
  • 5.  Variability: Is defined in the architecture through variation points, or a specific place in the architecture at which a feature can take one of two or more shapes.  Variability Sources:  In Function  In Data  In Technology  In Control Flow  In Environment  In Quality
  • 6. 4 Variation Patterns Pattern E.g. of Mechanism Binding Time Usage Product Architecture Derivation Configuration management, Generators Pre-build Implementation during the architecture & design phase Compilation Compiler Switches Pre-build Compiler flags will resolve to one binary output Linking Binary Replacement Pre-build Linkage with library/ binaries to produce one binary output Runtime Adoption during start up condition on variable Post-build Uses inline code to resolve variability at runtime.
  • 7. AUTOmotive Open System ARchitecture (AUTOSAR)  An open & standardized architecture for the automotive industry.  Jointly developed by the largest companies within the industry together with 3rd party suppliers & tool developers.  Aim to improve the way electronic equipment is developed, increase safety, performance & environmental friendliness.
  • 8.  Modules introduce in the standard  UML Meta Models  Annotated Meta Model  Extended Meta Model  4 patterns describe in the standard,  Aggregation Value Standard  Association Value Standard  Attribute Value Standard  Property Set Value Standard
  • 9. What is a Quality Tree??  Way of assessing & categorizing variant patterns used in an organization.  Leaf nodes represent strength &weaknesses discovered during the implementation.  Provide,  Guidance for the architect when making decisions for how to manage variability.  Good overview of the characteristics of one specific pattern.
  • 10. Mainly Focus Focus on key elements required to support run time variability using the AUTOSAR 4 .0 Standard through developing a prototype.
  • 11. Research Method There are 3 subsections,  Case setting  Data source.  Process
  • 12. Case Setting  Problem based on the Volvo Car’s preconceptions for managing variability to implement a variant mechanisms for run – time variability.  There are three stages in development that variants are used today at Volvo Cars. They are,  compilation mechanisms  local parameterization  distributed parameterization.
  • 13. Data Sources Sources Type Advantages Limitations Volvo cars component specification Document, architecture specification Valuable information based on refined domain knowledge. Restricted by confidentiality agreement. Volvo cars run-time variability specification Document ,architecture specification Valuable information based on refined domain knowledge. Draft document, may change. Restructured by confidentiality agreement. Software architect at Volvo cars Regular discussions 10 year of hand- on architect experience at Volvo cars Data is interpreted twice. AUTOSAR 4.0 specification Documents and UML meta-models Publicly available. Thorough and with examples. Difficult to address all relevant sections. Primary Sources Secondary Sources
  • 14. Process Under this step we can divided the implementation into three phases.  C Implementation - Written entirely in C  CAN-bus Implementation - Written entirely in C  AUTOSAR Implementation - Developed using AUTOSAR complaint tools.
  • 15. To assess the specification provided by Volvo cars.  First phase-: Intentionally avoided any use of “AUTOSAR”. Consequently this made it possible to discover what was required of the variant before making the prototype more true to the automotive environment.  Second phase-: Findings from the first phase were used to further refine the implementation towards the automotive industry.  Third phase-: Based on the findings with some limitations from the previous phases. The company started the development based on the following premises and requirements.  As much as possible takes place run-time.  A solution must be independent from the data it is supposed to pass.  Data used by a services does not have to be stored on the ECU where the service running.
  • 16. Research Data  The results outlined in this slides are coming from a prototype implementation of a run – time variability pattern.  Publisher-subscriber which is a mechanism for components, during application execution, to subscribe to state updates generated by another component, the so called publisher.  Volvo Cars' specification in its current state does not require subscription to take place in run-time.
  • 18. Phase 1: C Implementation
  • 19. Phase 2: CAN-bus Implementation
  • 20. Phase 3: AUTOSAR Implementation
  • 21. Quality Scenarios learnt during Implementation
  • 22.  Highlighted aspects derived during the development:  Subscription  Multiple Publishers  Push & Pull Strategies  Register Parameters of Interest  Local & Global configuration files  Parameters in an AUTOSAR environment
  • 24. Automotive Industry  Following factors have introduced for the motivation of variability in AUTOSAR.  Establish a common language to enable suppliers and manufactures to work together.  Use to avoid redundancy between artifacts.  It provides a basis for basic software product line.