SlideShare uma empresa Scribd logo
1 de 21
Baixar para ler offline
Visualiza<on	
  of	
  Traceability	
  Models	
  
  with	
  Domain-­‐specific	
  Layou<ng	
  

          Ábel	
  Hegedüs,	
  Zoltán  Ujhelyi,	
  
          István	
  Ráth	
  and	
  Ákos	
  Horváth	
  
  {hegedusa,ujhelyiz,rath,ahorvath}@mit.bme.hu	
  

   Budapest	
  University	
  of	
  Technology	
  and	
  Economics	
  
 Department	
  of	
  Measurements	
  and	
  Informa<on	
  Systems	
  
Mo<va<on	
  
  Verifica<on	
  transforma<on	
  for	
  BPEL	
  workflows	
  
   o Complex	
  transforma<on	
  
   o Traceability	
  model	
  automa<cally	
  generated	
  
       •  Proven	
  useful	
  during	
  transforma<on	
  debugging	
  


                                                    !()
                   Receive
                                                   * !"      $     %         '
     Input            Input
                     correct
             Yes    format?      No
                                                   ,- %                  &   '
         Copy                  Transform
                                                   + !"      #     %         '
    Output
                    Reply
Mo<va<on	
  
  Verifica<on	
  transforma<on	
  for	
  BPEL	
  workflows	
  
   o Complex	
  transforma<on	
  
   o Traceability	
  model	
  automa<cally	
  generated	
  
       •  Proven	
  useful	
  during	
  transforma<on	
  debugging	
  


                                                    !()
                   Receive
                                                   * !"      $     %         '
     Input            Input
                     correct
             Yes    format?      No
                                                   ,- %                  &   '
         Copy                  Transform
                                                   + !"      #     %         '
    Output
                    Reply
Visualiza<on	
  of	
  Traceability	
  Models	
  
  Goal:	
  integrated	
  visualiza<on	
  of…	
  
   o Traceability	
  records	
  and	
  
   o A	
  filtered	
  	
  version	
  of	
  the	
  source	
  and	
  target	
  model	
  
  Graph	
  display	
  
   o Model	
  Elements	
  as	
  Nodes	
  
   o Traceability	
  Rela<ons	
  as	
  Arcs	
  

                                      Traceability	
  
                                         model	
  
    Source	
                            element	
  
    model	
                                                                     Target	
  
   element	
                                                                    model	
  
                                                                               element	
  
Graph	
  layout	
  algorithms	
  
  Generic	
  Layout	
  Algorithms	
  
   o Considers	
  only	
  nodes	
  and	
  arcs	
  
   o Aesthe<c	
  criteria	
  op<miza<on	
  
  Domain-­‐specific	
  Layout	
  Algorithms	
  
   o Uses	
  model-­‐specific	
  informa<on	
  
Grid	
  Layout	
  
Spring	
  Layout	
  




Source-­‐Traceability-­‐
      Target	
  
  Model	
  Triplets	
  
Radial	
  Layout	
  
Radial	
  Layout	
  


            Traceability	
  
              Model	
  
Radial	
  Layout	
  
                  Source	
  and	
  Target	
  
                   Model	
  (Mixed)	
  
Requirements	
  
1.  Minimize	
  node  overlapping  
2.  Minimize	
  arc  crossing  
3.  Place	
  corresponding	
  model	
  elements	
  close  
4.  Separate	
  source,	
  target	
  and	
  traceability	
  models	
  
5.  Maintain	
  the  mental  map	
  during	
  changes	
  
Layout	
  for	
  traceability	
  visualiza<on	
  –	
  I.	
  
  Based	
  on	
  grid	
  layout	
  
    o Simple	
  layout	
  
    o Separa<on	
  of	
  model	
  parts	
  
    o No	
  node	
  overlapping	
  	
  
        •  Requirement	
  1.	
  ✔	
  
  Filters	
  
    o Based	
  on	
  type	
  rela<ons	
  
    o Removing	
  	
  intramodel	
  rela<ons	
  
Layout	
  for	
  traceability	
  visualiza<on	
  –	
  I.	
  
  Based	
  on	
  grid	
  layout	
  
    o Simple	
  layout	
  
             process:                recID:
                                        r_s          S2ID:     rece
    o Separa<on	
  of	
  model	
  identifier
             tProcess              parts	
         scope2id   tRec

    o No	
  node	
  overlapping	
  	
   r_t
               S2ID:               receive:         V2ID:     proc
        •  Requirement	
  1.	
  ✔	
   tReceive
             scope2id                               var2id    tPro
  Filters	
  
          sFinished:                inputID:        R2ID:       S2
    o Based	
  on	
  type	
  rela<ons	
  
           identifier              identifier       rec2id    scop
    o Removing	
  	
  intramodel	
  rela<ons	
  
                   input:        processID:                       V2
                 tVariable        identifier                      var
Layout	
  for	
  traceability	
  visualiza<on	
  –	
  II.	
  
  Ordering	
  
   o Placing	
  corresponding	
  elements	
  next	
  to	
  each	
  other	
  
       •  Requirement	
  3.	
  ✔	
  
   o Separates	
  source	
  and	
  target	
  model	
  elements	
  
       •  Requirement	
  4.	
  (Only	
  in	
  case	
  of	
  1:1	
  correspondence)	
  
   o Short	
  edges	
  –	
  Few	
  edge	
  crossings	
  
       •  Requirement	
  2.	
  ✔	
  
Layout	
  for	
  traceability	
  visualiza<on	
  –	
  II.	
  
      Ordering	
  
S2ID:           receive:               R2ID:             recID:                             rec
      o Placing	
  corresponding	
  elements	
  next	
  to	
  each	
  other	
  
ope2id         tReceive                rec2id          identifier                          tRe
         •  Requirement	
  3.	
  ✔	
  
V2ID: o Separates	
  source	
  and	
  target	
  model	
  elements	
  
               process:                     S2ID:                       processID:         pro
 ar2id   •  Requirement	
  4.	
  (Only	
  in	
  case	
  of	
  1:1	
  correspondence)	
  
               tProcess               scope2id                           identifier        tPr
         o Short	
  edges	
  –	
  Few	
  edge	
  crossings	
  
R2ID:                 S2ID:                 sFinished:                  input:               in
              •  Requirement	
  2.	
  ✔	
  
ec2id               scope2id                 identifier               tVariable            tVa

                        V2ID:                  inputID:
                        var2id                identifier
Layout	
  for	
  traceability	
  visualiza<on	
  –	
  II.	
  
  Ordering	
  
   o Placing	
  corresponding	
  elements	
  next	
  to	
  each	
  other	
  
       •  Requirement	
  3.	
  ✔	
  
   o Separates	
  source	
  and	
  target	
  model	
  elements	
  
       •  Requirement	
  4.	
  (Only	
  in	
  case	
  of	
  1:1	
  correspondence)	
  
   o Short	
  edges	
  –	
  Few	
  edge	
  crossings	
  
       •  Requirement	
  2.	
  ✔	
  
  Further	
  enhancements	
  
   o Handling	
  traceability	
  links	
  with	
  mul<ple	
  source	
  or	
  
     target	
  connec<ons	
  
       •  Requirement	
  4.	
  ✔	
  
Layout	
  for	
  traceability	
  visualiza<on	
  –	
  II.	
  
    Ordering	
  
D: o Placing	
  corresponding	
  elements	
  next	
  to	
  each	
  other	
  
           receive:                 R2ID:            recID:
ifier     tReceive
      •  Requirement	
  3.	
  ✔	
   rec2id      identifier

        o Separates	
  source	
  and	
  target	
  model	
  elements	
  
ssID:           process:                  S2ID:                           processID:
ifier       •  Requirement	
  4.	
  (Only	
  in	
  case	
  of	
  1:1	
  correspondence)	
  
                tProcess               scope2id                            identifier
        o Short	
  edges	
  –	
  Few	
  edge	
  crossings	
  
hed:        •  Requirement	
  2.	
  ✔	
       S2ID:                  sFinished:
ifier                                       scope2id                  identifier
    Further	
  enhancements	
  
tID: o Handling	
  traceability	
  links	
  with	
  mul<ple	
  source	
  or	
  
              input:                  V2ID:              inputID:
ifier  target	
  connec<ons	
   var2id
            tVariable                                   identifier
        •  Requirement	
  4.	
  ✔	
  
Integra<on	
  
  Graph	
  visualiza<on	
  component	
  for	
  VIATRA2	
  
   o User-­‐selected	
  model	
  elements	
  to	
  visualize	
  
   o Reacts	
  to	
  model	
  space	
  changes	
  
       •  Possibly	
  during	
  transforma<ons	
  
  Traceability	
  visualiza<on	
  
   o Domain-­‐specific	
  layout	
  algorithm	
  used	
  
   o Aeer	
  model	
  changes	
  relayou<ng	
  
DEMO  
Evalua<on	
  
  Poten<al	
  problems	
  
   o Informa<on	
  loss	
  
       •  Hiding	
  internal	
  structure	
  of	
  source	
  and	
  target	
  models	
  
   o Large	
  space	
  consump<on	
  
       •  A	
  row	
  is	
  required	
  for	
  every	
  traceability	
  record	
  
Conclusion	
  and	
  Future	
  Plans	
  
  Domain-­‐specific	
  layout	
  algorithm	
  
    o Traceability	
  models	
  
    o Fulfills	
  requirements	
  
    o Integrated	
  into	
  transforma<on	
  development	
  
      environment	
  
  Future	
  plans	
  
    o Displaying	
  structure	
  of	
  source/target	
  models	
  
    o Other	
  domain-­‐specific	
  visualiza<ons	
  

Mais conteúdo relacionado

Semelhante a Visualization of Traceability Models with Domain-specific Layouting

Challenges for advanced domain-specific frameworks
Challenges for advanced domain-specific frameworksChallenges for advanced domain-specific frameworks
Challenges for advanced domain-specific frameworksIstvan Rath
 
CeedMath & CeedGL, Let's talk 3D...
CeedMath & CeedGL, Let's talk 3D...CeedMath & CeedGL, Let's talk 3D...
CeedMath & CeedGL, Let's talk 3D...rsebbe
 
02 direct3 d_pipeline
02 direct3 d_pipeline02 direct3 d_pipeline
02 direct3 d_pipelineGirish Ghate
 
The operation principles of PVS-Studio static code analyzer
The operation principles of PVS-Studio static code analyzerThe operation principles of PVS-Studio static code analyzer
The operation principles of PVS-Studio static code analyzerAndrey Karpov
 
Synthetic Encoding
Synthetic EncodingSynthetic Encoding
Synthetic EncodingCheng LI
 
BADCamp 2008 DB Sync
BADCamp 2008 DB SyncBADCamp 2008 DB Sync
BADCamp 2008 DB SyncShaun Haber
 
웹표준 마크업 개발 프로세스
웹표준 마크업 개발 프로세스웹표준 마크업 개발 프로세스
웹표준 마크업 개발 프로세스webstandard
 
Bracket Show Episode 35 - histoire de c# de 2002 à 2019
Bracket Show Episode 35 - histoire de c# de 2002 à 2019Bracket Show Episode 35 - histoire de c# de 2002 à 2019
Bracket Show Episode 35 - histoire de c# de 2002 à 2019Eric De Carufel
 
Model-Driven Software Development - Strategies for Design & Implementation of...
Model-Driven Software Development - Strategies for Design & Implementation of...Model-Driven Software Development - Strategies for Design & Implementation of...
Model-Driven Software Development - Strategies for Design & Implementation of...Eelco Visser
 
Strategies for Design & Implementation of Domain-Specific Languages
Strategies for Design & Implementation of Domain-Specific LanguagesStrategies for Design & Implementation of Domain-Specific Languages
Strategies for Design & Implementation of Domain-Specific LanguagesEelco Visser
 
Code Analysis-run time error prediction
Code Analysis-run time error predictionCode Analysis-run time error prediction
Code Analysis-run time error predictionNIKHIL NAWATHE
 
Aspect Oriented Development
Aspect Oriented DevelopmentAspect Oriented Development
Aspect Oriented Developmenttyrantbrian
 
Consolidated shared indexes in real time
Consolidated shared indexes in real timeConsolidated shared indexes in real time
Consolidated shared indexes in real timeJeff Mace
 
Advanced Scenegraph Rendering Pipeline
Advanced Scenegraph Rendering PipelineAdvanced Scenegraph Rendering Pipeline
Advanced Scenegraph Rendering PipelineNarann29
 
Digging for Android Kernel Bugs
Digging for Android Kernel BugsDigging for Android Kernel Bugs
Digging for Android Kernel BugsJiahong Fang
 
1st UIM-GDB - Connections to the Real World
1st UIM-GDB - Connections to the Real World1st UIM-GDB - Connections to the Real World
1st UIM-GDB - Connections to the Real WorldAchim Friedland
 
Code Difference Visualization by a Call Tree
Code Difference Visualization by a Call TreeCode Difference Visualization by a Call Tree
Code Difference Visualization by a Call TreeKamiya Toshihiro
 
Hpg2011 papers kazakov
Hpg2011 papers kazakovHpg2011 papers kazakov
Hpg2011 papers kazakovmistercteam
 

Semelhante a Visualization of Traceability Models with Domain-specific Layouting (20)

Challenges for advanced domain-specific frameworks
Challenges for advanced domain-specific frameworksChallenges for advanced domain-specific frameworks
Challenges for advanced domain-specific frameworks
 
CeedMath & CeedGL, Let's talk 3D...
CeedMath & CeedGL, Let's talk 3D...CeedMath & CeedGL, Let's talk 3D...
CeedMath & CeedGL, Let's talk 3D...
 
02 direct3 d_pipeline
02 direct3 d_pipeline02 direct3 d_pipeline
02 direct3 d_pipeline
 
The operation principles of PVS-Studio static code analyzer
The operation principles of PVS-Studio static code analyzerThe operation principles of PVS-Studio static code analyzer
The operation principles of PVS-Studio static code analyzer
 
Synthetic Encoding
Synthetic EncodingSynthetic Encoding
Synthetic Encoding
 
BADCamp 2008 DB Sync
BADCamp 2008 DB SyncBADCamp 2008 DB Sync
BADCamp 2008 DB Sync
 
웹표준 마크업 개발 프로세스
웹표준 마크업 개발 프로세스웹표준 마크업 개발 프로세스
웹표준 마크업 개발 프로세스
 
Bracket Show Episode 35 - histoire de c# de 2002 à 2019
Bracket Show Episode 35 - histoire de c# de 2002 à 2019Bracket Show Episode 35 - histoire de c# de 2002 à 2019
Bracket Show Episode 35 - histoire de c# de 2002 à 2019
 
Model-Driven Software Development - Strategies for Design & Implementation of...
Model-Driven Software Development - Strategies for Design & Implementation of...Model-Driven Software Development - Strategies for Design & Implementation of...
Model-Driven Software Development - Strategies for Design & Implementation of...
 
Strategies for Design & Implementation of Domain-Specific Languages
Strategies for Design & Implementation of Domain-Specific LanguagesStrategies for Design & Implementation of Domain-Specific Languages
Strategies for Design & Implementation of Domain-Specific Languages
 
Code Analysis-run time error prediction
Code Analysis-run time error predictionCode Analysis-run time error prediction
Code Analysis-run time error prediction
 
Course File c++
Course File c++Course File c++
Course File c++
 
Aspect Oriented Development
Aspect Oriented DevelopmentAspect Oriented Development
Aspect Oriented Development
 
Consolidated shared indexes in real time
Consolidated shared indexes in real timeConsolidated shared indexes in real time
Consolidated shared indexes in real time
 
Advanced Scenegraph Rendering Pipeline
Advanced Scenegraph Rendering PipelineAdvanced Scenegraph Rendering Pipeline
Advanced Scenegraph Rendering Pipeline
 
Digging for Android Kernel Bugs
Digging for Android Kernel BugsDigging for Android Kernel Bugs
Digging for Android Kernel Bugs
 
1st UIM-GDB - Connections to the Real World
1st UIM-GDB - Connections to the Real World1st UIM-GDB - Connections to the Real World
1st UIM-GDB - Connections to the Real World
 
Code Difference Visualization by a Call Tree
Code Difference Visualization by a Call TreeCode Difference Visualization by a Call Tree
Code Difference Visualization by a Call Tree
 
Hpg2011 papers kazakov
Hpg2011 papers kazakovHpg2011 papers kazakov
Hpg2011 papers kazakov
 
Icpc08b.ppt
Icpc08b.pptIcpc08b.ppt
Icpc08b.ppt
 

Último

CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfsudhanshuwaghmare1
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsJoaquim Jorge
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 

Último (20)

CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 

Visualization of Traceability Models with Domain-specific Layouting

  • 1. Visualiza<on  of  Traceability  Models   with  Domain-­‐specific  Layou<ng   Ábel  Hegedüs,  Zoltán  Ujhelyi,   István  Ráth  and  Ákos  Horváth   {hegedusa,ujhelyiz,rath,ahorvath}@mit.bme.hu   Budapest  University  of  Technology  and  Economics   Department  of  Measurements  and  Informa<on  Systems  
  • 2. Mo<va<on     Verifica<on  transforma<on  for  BPEL  workflows   o Complex  transforma<on   o Traceability  model  automa<cally  generated   •  Proven  useful  during  transforma<on  debugging   !() Receive * !" $ % ' Input Input correct Yes format? No ,- % & ' Copy Transform + !" # % ' Output Reply
  • 3. Mo<va<on     Verifica<on  transforma<on  for  BPEL  workflows   o Complex  transforma<on   o Traceability  model  automa<cally  generated   •  Proven  useful  during  transforma<on  debugging   !() Receive * !" $ % ' Input Input correct Yes format? No ,- % & ' Copy Transform + !" # % ' Output Reply
  • 4. Visualiza<on  of  Traceability  Models     Goal:  integrated  visualiza<on  of…   o Traceability  records  and   o A  filtered    version  of  the  source  and  target  model     Graph  display   o Model  Elements  as  Nodes   o Traceability  Rela<ons  as  Arcs   Traceability   model   Source   element   model   Target   element   model   element  
  • 5. Graph  layout  algorithms     Generic  Layout  Algorithms   o Considers  only  nodes  and  arcs   o Aesthe<c  criteria  op<miza<on     Domain-­‐specific  Layout  Algorithms   o Uses  model-­‐specific  informa<on  
  • 9. Radial  Layout   Traceability   Model  
  • 10. Radial  Layout   Source  and  Target   Model  (Mixed)  
  • 11. Requirements   1.  Minimize  node  overlapping   2.  Minimize  arc  crossing   3.  Place  corresponding  model  elements  close   4.  Separate  source,  target  and  traceability  models   5.  Maintain  the  mental  map  during  changes  
  • 12. Layout  for  traceability  visualiza<on  –  I.     Based  on  grid  layout   o Simple  layout   o Separa<on  of  model  parts   o No  node  overlapping     •  Requirement  1.  ✔     Filters   o Based  on  type  rela<ons   o Removing    intramodel  rela<ons  
  • 13. Layout  for  traceability  visualiza<on  –  I.     Based  on  grid  layout   o Simple  layout   process: recID: r_s S2ID: rece o Separa<on  of  model  identifier tProcess parts   scope2id tRec o No  node  overlapping     r_t S2ID: receive: V2ID: proc •  Requirement  1.  ✔   tReceive scope2id var2id tPro   Filters   sFinished: inputID: R2ID: S2 o Based  on  type  rela<ons   identifier identifier rec2id scop o Removing    intramodel  rela<ons   input: processID: V2 tVariable identifier var
  • 14. Layout  for  traceability  visualiza<on  –  II.     Ordering   o Placing  corresponding  elements  next  to  each  other   •  Requirement  3.  ✔   o Separates  source  and  target  model  elements   •  Requirement  4.  (Only  in  case  of  1:1  correspondence)   o Short  edges  –  Few  edge  crossings   •  Requirement  2.  ✔  
  • 15. Layout  for  traceability  visualiza<on  –  II.     Ordering   S2ID: receive: R2ID: recID: rec o Placing  corresponding  elements  next  to  each  other   ope2id tReceive rec2id identifier tRe •  Requirement  3.  ✔   V2ID: o Separates  source  and  target  model  elements   process: S2ID: processID: pro ar2id •  Requirement  4.  (Only  in  case  of  1:1  correspondence)   tProcess scope2id identifier tPr o Short  edges  –  Few  edge  crossings   R2ID: S2ID: sFinished: input: in •  Requirement  2.  ✔   ec2id scope2id identifier tVariable tVa V2ID: inputID: var2id identifier
  • 16. Layout  for  traceability  visualiza<on  –  II.     Ordering   o Placing  corresponding  elements  next  to  each  other   •  Requirement  3.  ✔   o Separates  source  and  target  model  elements   •  Requirement  4.  (Only  in  case  of  1:1  correspondence)   o Short  edges  –  Few  edge  crossings   •  Requirement  2.  ✔     Further  enhancements   o Handling  traceability  links  with  mul<ple  source  or   target  connec<ons   •  Requirement  4.  ✔  
  • 17. Layout  for  traceability  visualiza<on  –  II.     Ordering   D: o Placing  corresponding  elements  next  to  each  other   receive: R2ID: recID: ifier tReceive •  Requirement  3.  ✔   rec2id identifier o Separates  source  and  target  model  elements   ssID: process: S2ID: processID: ifier •  Requirement  4.  (Only  in  case  of  1:1  correspondence)   tProcess scope2id identifier o Short  edges  –  Few  edge  crossings   hed: •  Requirement  2.  ✔   S2ID: sFinished: ifier scope2id identifier   Further  enhancements   tID: o Handling  traceability  links  with  mul<ple  source  or   input: V2ID: inputID: ifier target  connec<ons   var2id tVariable identifier •  Requirement  4.  ✔  
  • 18. Integra<on     Graph  visualiza<on  component  for  VIATRA2   o User-­‐selected  model  elements  to  visualize   o Reacts  to  model  space  changes   •  Possibly  during  transforma<ons     Traceability  visualiza<on   o Domain-­‐specific  layout  algorithm  used   o Aeer  model  changes  relayou<ng  
  • 20. Evalua<on     Poten<al  problems   o Informa<on  loss   •  Hiding  internal  structure  of  source  and  target  models   o Large  space  consump<on   •  A  row  is  required  for  every  traceability  record  
  • 21. Conclusion  and  Future  Plans     Domain-­‐specific  layout  algorithm   o Traceability  models   o Fulfills  requirements   o Integrated  into  transforma<on  development   environment     Future  plans   o Displaying  structure  of  source/target  models   o Other  domain-­‐specific  visualiza<ons