SlideShare uma empresa Scribd logo
1 de 33
Searching
 for Key Stakeholders in
 Large-Scale Software Projects


Soo Ling Lim
University College London


                      13th CREST Open Workshop
                             12 May 2011
What makes developers cry?
                   can't communicate
                    with stakeholders
  can't maintain
                                                       541 developers
  stakeholders




      can't find
    stakeholders                   stakeholders lack
                                         skill




         stakeholders lack
            commitment                                 I.
Alexander
&
S.
Robertson

                                                       (2004)
Understanding

                                                       Project
Sociology
by

                                                       Modeling
Stakeholders.


                                                       IEEE
SoCware.

Identify   Prioritise
S.L.
Lim,
D.
Quercia
&
A.
Finkelstein
(2010)
StakeNet:
Using
Social
Networks
to
Analyse

the
stakeholders
of
Large‐Scale
SoGware
Projects.
In
32nd
Int.
Conf.
on
SoG.
Eng.
(ICSE).

Step 1: Find initial stakeholders




    Users           Developers




  Legislators    Decision-makers
Step 2: Get recommendations
Step 2: Get recommendations


      <Alice, Director of Estates, 4>
Step 3: Build social network
Step 3: Build social network




              Alice
Step 3: Build social network

          Bob


                        Carl
                Alice
Step 3: Build social network

          Bob


                        Carl
                Alice
Step 4: Elicit requirements

         Bob


                       Carl
               Alice
Step 5: Prioritise requirements
               n
ImportanceR = ∑ ProjectInfluenceS × RatingS
              S=1
Step 5: Prioritise requirements
                                n
ImportanceR = ∑ ProjectInfluenceS × RatingS
                              S=1




                                    Use
social
network
measures,
e.g.,

                                    • 
Betweenness
centrality

                                    • 
PageRank

                                    • 
Out‐degree
centrality

                                    • 
In‐degree
centrality



S.L.
Lim
&
A.
Finkelstein
(2011)
StakeRare:
Social
Networks
and
CollaboraLve
Filtering
for

Large‐Scale
Requirements
ElicitaLon.
IEEE
TransacLons
on
SoCware
Engineering
(TSE).

Step 5: Prioritise requirements
                       0.81

             0.70

                                             0.58

                                    0.56

                                                           0.49
    0.48





S.L.
Lim
&
A.
Finkelstein
(2011)
StakeRare:
Social
Networks
and
CollaboraLve
Filtering
for

Large‐Scale
Requirements
ElicitaLon.
IEEE
TransacLons
on
SoCware
Engineering
(TSE).

Step 5: Prioritise requirements
                       0.81
                               n
                                            ImportanceR = ∑ ProjectInfluenceS × RatingS
             0.70
                                        S=1


                                               0.58

                                    0.56

                               €                           0.49
    0.48





S.L.
Lim
&
A.
Finkelstein
(2011)
StakeRare:
Social
Networks
and
CollaboraLve
Filtering
for

Large‐Scale
Requirements
ElicitaLon.
IEEE
TransacLons
on
SoCware
Engineering
(TSE).

Use a genetic algorithm
                            to search for
                           real influence
                  GA to search for weights


S.L.
Lim,
M.
Harman
&
A.
Susi.
Searching
for
Key
Stakeholders
in
Large‐Scale

SoCware
Projects
(submiVed).

Step 5: Prioritise requirements
               n
ImportanceR = ∑ ProjectInfluenceS × RatingS
              S=1
Step 5: Prioritise requirements
                     n
 ImportanceR = ∑ ProjectInfluenceS × RatingS
                    S=1

  Actual importance
(Based on post project
     knowledge)
Step 5: Prioritise requirements
                     n
 ImportanceR = ∑ ProjectInfluenceS × RatingS
                    S=1

  Actual importance
(Based on post project
     knowledge)
RALIC: UCL Access Control Project
Ratings
Data Set
•  ~150 requirements
•  68 stakeholders recommended other
   stakeholders
•  76 stakeholders provided ratings
•  actual ranked list of requirements based
   on post project knowledge
Findings
•  Existing social network measures can be
   used to prioritise stakeholders….but they
   are not optimal and may miss out key
   stakeholders (GA can always improve
   them).
•  Evolution corrected assumptions made by
   the measures that don’t hold for the
   stakeholder.
Findings
•  The GA found many good solutions
  –  A good set of requirements can be constructed
     from many different subsets of stakeholders
•  Some stakeholders hold unique knowledge
   (always selected by the GA), but the majority
   of stakeholders share similar knowledge
   (replaceable)
•  The concept of who is a “key stakeholder”
   depends on which other stakeholders have
   already been identified.
Soo
Ling
Lim

s.lim@cs.ucl.ac.uk


Mais conteúdo relacionado

Mais procurados

Interventionist-methods - Methods in user-technology studies
Interventionist-methods - Methods in user-technology studiesInterventionist-methods - Methods in user-technology studies
Interventionist-methods - Methods in user-technology studiesAntti Salovaara
 
Uncovering hidden relationships from past changes: evolutionary dependencies ...
Uncovering hidden relationships from past changes: evolutionary dependencies ...Uncovering hidden relationships from past changes: evolutionary dependencies ...
Uncovering hidden relationships from past changes: evolutionary dependencies ...Marco Aurelio Gerosa
 
Findability through Traceability - A Realistic Application of Candidate Tr...
Findability through Traceability  - A Realistic Application of Candidate Tr...Findability through Traceability  - A Realistic Application of Candidate Tr...
Findability through Traceability - A Realistic Application of Candidate Tr...Markus Borg
 
Characterizing and Detecting Integrity Issues in OWL Instance Data
Characterizing and Detecting Integrity Issues in OWL Instance DataCharacterizing and Detecting Integrity Issues in OWL Instance Data
Characterizing and Detecting Integrity Issues in OWL Instance DataJie Bao
 
Stratosphere project: free software machine learning to protect ng os
Stratosphere project: free software machine learning to protect ng osStratosphere project: free software machine learning to protect ng os
Stratosphere project: free software machine learning to protect ng osCzech Technical University in Prague
 
Mining Software Repositories
Mining Software RepositoriesMining Software Repositories
Mining Software RepositoriesIsrael Herraiz
 
The Onion Patch: Migration in Open Source Ecosystems
The Onion Patch: Migration in Open Source EcosystemsThe Onion Patch: Migration in Open Source Ecosystems
The Onion Patch: Migration in Open Source EcosystemsPatrick Wagstrom
 

Mais procurados (8)

Interventionist-methods - Methods in user-technology studies
Interventionist-methods - Methods in user-technology studiesInterventionist-methods - Methods in user-technology studies
Interventionist-methods - Methods in user-technology studies
 
Uncovering hidden relationships from past changes: evolutionary dependencies ...
Uncovering hidden relationships from past changes: evolutionary dependencies ...Uncovering hidden relationships from past changes: evolutionary dependencies ...
Uncovering hidden relationships from past changes: evolutionary dependencies ...
 
Findability through Traceability - A Realistic Application of Candidate Tr...
Findability through Traceability  - A Realistic Application of Candidate Tr...Findability through Traceability  - A Realistic Application of Candidate Tr...
Findability through Traceability - A Realistic Application of Candidate Tr...
 
Characterizing and Detecting Integrity Issues in OWL Instance Data
Characterizing and Detecting Integrity Issues in OWL Instance DataCharacterizing and Detecting Integrity Issues in OWL Instance Data
Characterizing and Detecting Integrity Issues in OWL Instance Data
 
Stratosphere project: free software machine learning to protect ng os
Stratosphere project: free software machine learning to protect ng osStratosphere project: free software machine learning to protect ng os
Stratosphere project: free software machine learning to protect ng os
 
Jerald Dawson Resume
Jerald Dawson ResumeJerald Dawson Resume
Jerald Dawson Resume
 
Mining Software Repositories
Mining Software RepositoriesMining Software Repositories
Mining Software Repositories
 
The Onion Patch: Migration in Open Source Ecosystems
The Onion Patch: Migration in Open Source EcosystemsThe Onion Patch: Migration in Open Source Ecosystems
The Onion Patch: Migration in Open Source Ecosystems
 

Destaque

Visual Exploration of Large-Scale Evolving Software
Visual Exploration of Large-Scale Evolving SoftwareVisual Exploration of Large-Scale Evolving Software
Visual Exploration of Large-Scale Evolving SoftwareRichard Wettel
 
Large scale software development
Large scale software development Large scale software development
Large scale software development mahamiqbalrajput
 
User Requirements in Audiovisual Search: a Quantitative Approach
User Requirements in Audiovisual Search: a Quantitative ApproachUser Requirements in Audiovisual Search: a Quantitative Approach
User Requirements in Audiovisual Search: a Quantitative Approachroelandordelman.nl
 
How to market your app
How to market your appHow to market your app
How to market your appSoo Ling Lim
 
Jan-Erik Sandberg - Succeeding with Large Scale Agile
Jan-Erik Sandberg - Succeeding with Large Scale AgileJan-Erik Sandberg - Succeeding with Large Scale Agile
Jan-Erik Sandberg - Succeeding with Large Scale AgileAgile Lietuva
 
Introducing TensorFlow: The game changer in building "intelligent" applications
Introducing TensorFlow: The game changer in building "intelligent" applicationsIntroducing TensorFlow: The game changer in building "intelligent" applications
Introducing TensorFlow: The game changer in building "intelligent" applicationsRokesh Jankie
 
Software Design Practices for Large-Scale Automation
Software Design Practices for Large-Scale AutomationSoftware Design Practices for Large-Scale Automation
Software Design Practices for Large-Scale AutomationHao Xu
 

Destaque (7)

Visual Exploration of Large-Scale Evolving Software
Visual Exploration of Large-Scale Evolving SoftwareVisual Exploration of Large-Scale Evolving Software
Visual Exploration of Large-Scale Evolving Software
 
Large scale software development
Large scale software development Large scale software development
Large scale software development
 
User Requirements in Audiovisual Search: a Quantitative Approach
User Requirements in Audiovisual Search: a Quantitative ApproachUser Requirements in Audiovisual Search: a Quantitative Approach
User Requirements in Audiovisual Search: a Quantitative Approach
 
How to market your app
How to market your appHow to market your app
How to market your app
 
Jan-Erik Sandberg - Succeeding with Large Scale Agile
Jan-Erik Sandberg - Succeeding with Large Scale AgileJan-Erik Sandberg - Succeeding with Large Scale Agile
Jan-Erik Sandberg - Succeeding with Large Scale Agile
 
Introducing TensorFlow: The game changer in building "intelligent" applications
Introducing TensorFlow: The game changer in building "intelligent" applicationsIntroducing TensorFlow: The game changer in building "intelligent" applications
Introducing TensorFlow: The game changer in building "intelligent" applications
 
Software Design Practices for Large-Scale Automation
Software Design Practices for Large-Scale AutomationSoftware Design Practices for Large-Scale Automation
Software Design Practices for Large-Scale Automation
 

Semelhante a Finding Key Stakeholders in Large Software Projects Using Social Network Analysis and Genetic Algorithms

Analysis of software architectures
Analysis of software architecturesAnalysis of software architectures
Analysis of software architecturesHoria Constantin
 
Seams2016 presentation calikli_et_al
Seams2016 presentation calikli_et_alSeams2016 presentation calikli_et_al
Seams2016 presentation calikli_et_alGul Calikli
 
The IoT Methodology & An Introduction to the Intel Galileo, Edison and SmartL...
The IoT Methodology & An Introduction to the Intel Galileo, Edison and SmartL...The IoT Methodology & An Introduction to the Intel Galileo, Edison and SmartL...
The IoT Methodology & An Introduction to the Intel Galileo, Edison and SmartL...The Internet of Things Methodology
 
Immersive Recommendation
Immersive RecommendationImmersive Recommendation
Immersive Recommendation承剛 謝
 
ICSME 2016 keynote: An ecosystemic and socio-technical view on software maint...
ICSME 2016 keynote: An ecosystemic and socio-technical view on software maint...ICSME 2016 keynote: An ecosystemic and socio-technical view on software maint...
ICSME 2016 keynote: An ecosystemic and socio-technical view on software maint...Tom Mens
 
Who models the world? Collaborative ontology creation and user roles in Wikidata
Who models the world? Collaborative ontology creation and user roles in WikidataWho models the world? Collaborative ontology creation and user roles in Wikidata
Who models the world? Collaborative ontology creation and user roles in WikidataAlessandro Piscopo
 
Adding Semantics to Social Software Engineering (by Steffen Lohmann & Thomas ...
Adding Semantics to Social Software Engineering (by Steffen Lohmann & Thomas ...Adding Semantics to Social Software Engineering (by Steffen Lohmann & Thomas ...
Adding Semantics to Social Software Engineering (by Steffen Lohmann & Thomas ...Wolfgang Reinhardt
 
Relationships Matter: Using Connected Data for Better Machine Learning
Relationships Matter: Using Connected Data for Better Machine LearningRelationships Matter: Using Connected Data for Better Machine Learning
Relationships Matter: Using Connected Data for Better Machine LearningNeo4j
 
Landscape of IoT and Machine Learning Patterns
Landscape of IoT and Machine Learning PatternsLandscape of IoT and Machine Learning Patterns
Landscape of IoT and Machine Learning PatternsHironori Washizaki
 
DevOps Support for an Ethical Software Development Life Cycle (SDLC)
DevOps Support for an Ethical Software Development Life Cycle (SDLC)DevOps Support for an Ethical Software Development Life Cycle (SDLC)
DevOps Support for an Ethical Software Development Life Cycle (SDLC)Mark Underwood
 
The Social Requirements Engineering (SRE) Approach to Developing a Large-scal...
The Social Requirements Engineering (SRE) Approach to Developing a Large-scal...The Social Requirements Engineering (SRE) Approach to Developing a Large-scal...
The Social Requirements Engineering (SRE) Approach to Developing a Large-scal...Ralf Klamma
 
TruSIS: Trust Accross Social Network
TruSIS: Trust Accross Social NetworkTruSIS: Trust Accross Social Network
TruSIS: Trust Accross Social NetworkLora Aroyo
 
06 styles and_greenfield_design
06 styles and_greenfield_design06 styles and_greenfield_design
06 styles and_greenfield_designMajong DevJfu
 

Semelhante a Finding Key Stakeholders in Large Software Projects Using Social Network Analysis and Genetic Algorithms (20)

Analysis of software architectures
Analysis of software architecturesAnalysis of software architectures
Analysis of software architectures
 
Seams2016 presentation calikli_et_al
Seams2016 presentation calikli_et_alSeams2016 presentation calikli_et_al
Seams2016 presentation calikli_et_al
 
The IoT Methodology & An Introduction to the Intel Galileo, Edison and SmartL...
The IoT Methodology & An Introduction to the Intel Galileo, Edison and SmartL...The IoT Methodology & An Introduction to the Intel Galileo, Edison and SmartL...
The IoT Methodology & An Introduction to the Intel Galileo, Edison and SmartL...
 
Immersive Recommendation
Immersive RecommendationImmersive Recommendation
Immersive Recommendation
 
Unit 5
Unit 5Unit 5
Unit 5
 
ICSME 2016 keynote: An ecosystemic and socio-technical view on software maint...
ICSME 2016 keynote: An ecosystemic and socio-technical view on software maint...ICSME 2016 keynote: An ecosystemic and socio-technical view on software maint...
ICSME 2016 keynote: An ecosystemic and socio-technical view on software maint...
 
Data-X-v3.1
Data-X-v3.1Data-X-v3.1
Data-X-v3.1
 
A Methodology for Building the Internet of Things
A Methodology for Building the Internet of ThingsA Methodology for Building the Internet of Things
A Methodology for Building the Internet of Things
 
Who models the world? Collaborative ontology creation and user roles in Wikidata
Who models the world? Collaborative ontology creation and user roles in WikidataWho models the world? Collaborative ontology creation and user roles in Wikidata
Who models the world? Collaborative ontology creation and user roles in Wikidata
 
Adding Semantics to Social Software Engineering (by Steffen Lohmann & Thomas ...
Adding Semantics to Social Software Engineering (by Steffen Lohmann & Thomas ...Adding Semantics to Social Software Engineering (by Steffen Lohmann & Thomas ...
Adding Semantics to Social Software Engineering (by Steffen Lohmann & Thomas ...
 
Relationships Matter: Using Connected Data for Better Machine Learning
Relationships Matter: Using Connected Data for Better Machine LearningRelationships Matter: Using Connected Data for Better Machine Learning
Relationships Matter: Using Connected Data for Better Machine Learning
 
Landscape of IoT and Machine Learning Patterns
Landscape of IoT and Machine Learning PatternsLandscape of IoT and Machine Learning Patterns
Landscape of IoT and Machine Learning Patterns
 
DevOps Support for an Ethical Software Development Life Cycle (SDLC)
DevOps Support for an Ethical Software Development Life Cycle (SDLC)DevOps Support for an Ethical Software Development Life Cycle (SDLC)
DevOps Support for an Ethical Software Development Life Cycle (SDLC)
 
Data-X-Sparse-v2
Data-X-Sparse-v2Data-X-Sparse-v2
Data-X-Sparse-v2
 
The Social Requirements Engineering (SRE) Approach to Developing a Large-scal...
The Social Requirements Engineering (SRE) Approach to Developing a Large-scal...The Social Requirements Engineering (SRE) Approach to Developing a Large-scal...
The Social Requirements Engineering (SRE) Approach to Developing a Large-scal...
 
Metrics in virtual worlds
Metrics in virtual worldsMetrics in virtual worlds
Metrics in virtual worlds
 
TruSIS: Trust Accross Social Network
TruSIS: Trust Accross Social NetworkTruSIS: Trust Accross Social Network
TruSIS: Trust Accross Social Network
 
Promise notes
Promise notesPromise notes
Promise notes
 
06 styles and_greenfield_design
06 styles and_greenfield_design06 styles and_greenfield_design
06 styles and_greenfield_design
 
An influence propagation view of page rank
An influence propagation view of page rankAn influence propagation view of page rank
An influence propagation view of page rank
 

Último

Best VIP Call Girls Noida Sector 40 Call Me: 8448380779
Best VIP Call Girls Noida Sector 40 Call Me: 8448380779Best VIP Call Girls Noida Sector 40 Call Me: 8448380779
Best VIP Call Girls Noida Sector 40 Call Me: 8448380779Delhi Call girls
 
Cash Payment 9602870969 Escort Service in Udaipur Call Girls
Cash Payment 9602870969 Escort Service in Udaipur Call GirlsCash Payment 9602870969 Escort Service in Udaipur Call Girls
Cash Payment 9602870969 Escort Service in Udaipur Call GirlsApsara Of India
 
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...Any kyc Account
 
M.C Lodges -- Guest House in Jhang.
M.C Lodges --  Guest House in Jhang.M.C Lodges --  Guest House in Jhang.
M.C Lodges -- Guest House in Jhang.Aaiza Hassan
 
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...Dave Litwiller
 
Pharma Works Profile of Karan Communications
Pharma Works Profile of Karan CommunicationsPharma Works Profile of Karan Communications
Pharma Works Profile of Karan Communicationskarancommunications
 
Insurers' journeys to build a mastery in the IoT usage
Insurers' journeys to build a mastery in the IoT usageInsurers' journeys to build a mastery in the IoT usage
Insurers' journeys to build a mastery in the IoT usageMatteo Carbone
 
Event mailer assignment progress report .pdf
Event mailer assignment progress report .pdfEvent mailer assignment progress report .pdf
Event mailer assignment progress report .pdftbatkhuu1
 
Sales & Marketing Alignment: How to Synergize for Success
Sales & Marketing Alignment: How to Synergize for SuccessSales & Marketing Alignment: How to Synergize for Success
Sales & Marketing Alignment: How to Synergize for SuccessAggregage
 
Russian Faridabad Call Girls(Badarpur) : ☎ 8168257667, @4999
Russian Faridabad Call Girls(Badarpur) : ☎ 8168257667, @4999Russian Faridabad Call Girls(Badarpur) : ☎ 8168257667, @4999
Russian Faridabad Call Girls(Badarpur) : ☎ 8168257667, @4999Tina Ji
 
0183760ssssssssssssssssssssssssssss00101011 (27).pdf
0183760ssssssssssssssssssssssssssss00101011 (27).pdf0183760ssssssssssssssssssssssssssss00101011 (27).pdf
0183760ssssssssssssssssssssssssssss00101011 (27).pdfRenandantas16
 
Regression analysis: Simple Linear Regression Multiple Linear Regression
Regression analysis:  Simple Linear Regression Multiple Linear RegressionRegression analysis:  Simple Linear Regression Multiple Linear Regression
Regression analysis: Simple Linear Regression Multiple Linear RegressionRavindra Nath Shukla
 
HONOR Veterans Event Keynote by Michael Hawkins
HONOR Veterans Event Keynote by Michael HawkinsHONOR Veterans Event Keynote by Michael Hawkins
HONOR Veterans Event Keynote by Michael HawkinsMichael W. Hawkins
 
7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...Paul Menig
 
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...Lviv Startup Club
 
Grateful 7 speech thanking everyone that has helped.pdf
Grateful 7 speech thanking everyone that has helped.pdfGrateful 7 speech thanking everyone that has helped.pdf
Grateful 7 speech thanking everyone that has helped.pdfPaul Menig
 
GD Birla and his contribution in management
GD Birla and his contribution in managementGD Birla and his contribution in management
GD Birla and his contribution in managementchhavia330
 
Keppel Ltd. 1Q 2024 Business Update Presentation Slides
Keppel Ltd. 1Q 2024 Business Update  Presentation SlidesKeppel Ltd. 1Q 2024 Business Update  Presentation Slides
Keppel Ltd. 1Q 2024 Business Update Presentation SlidesKeppelCorporation
 
BEST ✨ Call Girls In Indirapuram Ghaziabad ✔️ 9871031762 ✔️ Escorts Service...
BEST ✨ Call Girls In  Indirapuram Ghaziabad  ✔️ 9871031762 ✔️ Escorts Service...BEST ✨ Call Girls In  Indirapuram Ghaziabad  ✔️ 9871031762 ✔️ Escorts Service...
BEST ✨ Call Girls In Indirapuram Ghaziabad ✔️ 9871031762 ✔️ Escorts Service...noida100girls
 

Último (20)

Best VIP Call Girls Noida Sector 40 Call Me: 8448380779
Best VIP Call Girls Noida Sector 40 Call Me: 8448380779Best VIP Call Girls Noida Sector 40 Call Me: 8448380779
Best VIP Call Girls Noida Sector 40 Call Me: 8448380779
 
Cash Payment 9602870969 Escort Service in Udaipur Call Girls
Cash Payment 9602870969 Escort Service in Udaipur Call GirlsCash Payment 9602870969 Escort Service in Udaipur Call Girls
Cash Payment 9602870969 Escort Service in Udaipur Call Girls
 
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...
KYC-Verified Accounts: Helping Companies Handle Challenging Regulatory Enviro...
 
M.C Lodges -- Guest House in Jhang.
M.C Lodges --  Guest House in Jhang.M.C Lodges --  Guest House in Jhang.
M.C Lodges -- Guest House in Jhang.
 
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...
 
Pharma Works Profile of Karan Communications
Pharma Works Profile of Karan CommunicationsPharma Works Profile of Karan Communications
Pharma Works Profile of Karan Communications
 
Insurers' journeys to build a mastery in the IoT usage
Insurers' journeys to build a mastery in the IoT usageInsurers' journeys to build a mastery in the IoT usage
Insurers' journeys to build a mastery in the IoT usage
 
Event mailer assignment progress report .pdf
Event mailer assignment progress report .pdfEvent mailer assignment progress report .pdf
Event mailer assignment progress report .pdf
 
Sales & Marketing Alignment: How to Synergize for Success
Sales & Marketing Alignment: How to Synergize for SuccessSales & Marketing Alignment: How to Synergize for Success
Sales & Marketing Alignment: How to Synergize for Success
 
Russian Faridabad Call Girls(Badarpur) : ☎ 8168257667, @4999
Russian Faridabad Call Girls(Badarpur) : ☎ 8168257667, @4999Russian Faridabad Call Girls(Badarpur) : ☎ 8168257667, @4999
Russian Faridabad Call Girls(Badarpur) : ☎ 8168257667, @4999
 
0183760ssssssssssssssssssssssssssss00101011 (27).pdf
0183760ssssssssssssssssssssssssssss00101011 (27).pdf0183760ssssssssssssssssssssssssssss00101011 (27).pdf
0183760ssssssssssssssssssssssssssss00101011 (27).pdf
 
Regression analysis: Simple Linear Regression Multiple Linear Regression
Regression analysis:  Simple Linear Regression Multiple Linear RegressionRegression analysis:  Simple Linear Regression Multiple Linear Regression
Regression analysis: Simple Linear Regression Multiple Linear Regression
 
HONOR Veterans Event Keynote by Michael Hawkins
HONOR Veterans Event Keynote by Michael HawkinsHONOR Veterans Event Keynote by Michael Hawkins
HONOR Veterans Event Keynote by Michael Hawkins
 
7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...
 
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
 
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...
 
Grateful 7 speech thanking everyone that has helped.pdf
Grateful 7 speech thanking everyone that has helped.pdfGrateful 7 speech thanking everyone that has helped.pdf
Grateful 7 speech thanking everyone that has helped.pdf
 
GD Birla and his contribution in management
GD Birla and his contribution in managementGD Birla and his contribution in management
GD Birla and his contribution in management
 
Keppel Ltd. 1Q 2024 Business Update Presentation Slides
Keppel Ltd. 1Q 2024 Business Update  Presentation SlidesKeppel Ltd. 1Q 2024 Business Update  Presentation Slides
Keppel Ltd. 1Q 2024 Business Update Presentation Slides
 
BEST ✨ Call Girls In Indirapuram Ghaziabad ✔️ 9871031762 ✔️ Escorts Service...
BEST ✨ Call Girls In  Indirapuram Ghaziabad  ✔️ 9871031762 ✔️ Escorts Service...BEST ✨ Call Girls In  Indirapuram Ghaziabad  ✔️ 9871031762 ✔️ Escorts Service...
BEST ✨ Call Girls In Indirapuram Ghaziabad ✔️ 9871031762 ✔️ Escorts Service...
 

Finding Key Stakeholders in Large Software Projects Using Social Network Analysis and Genetic Algorithms

  • 1. Searching for Key Stakeholders in Large-Scale Software Projects Soo Ling Lim University College London 13th CREST Open Workshop 12 May 2011
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7. What makes developers cry? can't communicate with stakeholders can't maintain 541 developers stakeholders can't find stakeholders stakeholders lack skill stakeholders lack commitment I.
Alexander
&
S.
Robertson
 (2004)
Understanding
 Project
Sociology
by
 Modeling
Stakeholders.

 IEEE
SoCware.

  • 8. Identify Prioritise
  • 10. Step 1: Find initial stakeholders Users Developers Legislators Decision-makers
  • 11. Step 2: Get recommendations
  • 12. Step 2: Get recommendations <Alice, Director of Estates, 4>
  • 13. Step 3: Build social network
  • 14. Step 3: Build social network Alice
  • 15. Step 3: Build social network Bob Carl Alice
  • 16. Step 3: Build social network Bob Carl Alice
  • 17. Step 4: Elicit requirements Bob Carl Alice
  • 18. Step 5: Prioritise requirements n ImportanceR = ∑ ProjectInfluenceS × RatingS S=1
  • 19. Step 5: Prioritise requirements n ImportanceR = ∑ ProjectInfluenceS × RatingS S=1 Use
social
network
measures,
e.g.,
 • 
Betweenness
centrality
 • 
PageRank
 • 
Out‐degree
centrality
 • 
In‐degree
centrality
 S.L.
Lim
&
A.
Finkelstein
(2011)
StakeRare:
Social
Networks
and
CollaboraLve
Filtering
for
 Large‐Scale
Requirements
ElicitaLon.
IEEE
TransacLons
on
SoCware
Engineering
(TSE).

  • 20. Step 5: Prioritise requirements 0.81
 0.70
 0.58
 0.56
 0.49
 0.48
 S.L.
Lim
&
A.
Finkelstein
(2011)
StakeRare:
Social
Networks
and
CollaboraLve
Filtering
for
 Large‐Scale
Requirements
ElicitaLon.
IEEE
TransacLons
on
SoCware
Engineering
(TSE).

  • 21. Step 5: Prioritise requirements 0.81
 n ImportanceR = ∑ ProjectInfluenceS × RatingS 0.70
 S=1 0.58
 0.56
 € 0.49
 0.48
 S.L.
Lim
&
A.
Finkelstein
(2011)
StakeRare:
Social
Networks
and
CollaboraLve
Filtering
for
 Large‐Scale
Requirements
ElicitaLon.
IEEE
TransacLons
on
SoCware
Engineering
(TSE).

  • 22. Use a genetic algorithm to search for real influence GA to search for weights S.L.
Lim,
M.
Harman
&
A.
Susi.
Searching
for
Key
Stakeholders
in
Large‐Scale
 SoCware
Projects
(submiVed).

  • 23. Step 5: Prioritise requirements n ImportanceR = ∑ ProjectInfluenceS × RatingS S=1
  • 24. Step 5: Prioritise requirements n ImportanceR = ∑ ProjectInfluenceS × RatingS S=1 Actual importance (Based on post project knowledge)
  • 25. Step 5: Prioritise requirements n ImportanceR = ∑ ProjectInfluenceS × RatingS S=1 Actual importance (Based on post project knowledge)
  • 26. RALIC: UCL Access Control Project
  • 27.
  • 29. Data Set •  ~150 requirements •  68 stakeholders recommended other stakeholders •  76 stakeholders provided ratings •  actual ranked list of requirements based on post project knowledge
  • 30. Findings •  Existing social network measures can be used to prioritise stakeholders….but they are not optimal and may miss out key stakeholders (GA can always improve them). •  Evolution corrected assumptions made by the measures that don’t hold for the stakeholder.
  • 31. Findings •  The GA found many good solutions –  A good set of requirements can be constructed from many different subsets of stakeholders •  Some stakeholders hold unique knowledge (always selected by the GA), but the majority of stakeholders share similar knowledge (replaceable) •  The concept of who is a “key stakeholder” depends on which other stakeholders have already been identified.
  • 32.

Notas do Editor

  1. 22
  2. What is the relationship