Expert mining compsac-2014
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The document outlines a workshop procedure for assessing risk indicators in open source software adoption, focusing on the RISCOSS analytics platform and tactical workshops involving domain experts. It details the steps involved in preparing for these workshops, managing risks, and evaluating scenarios using statistical tools and expert judgments. Additionally, it highlights applications and lessons learned from past workshops conducted in various countries.
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Tacticalworkshop
protocol
Workshop procedure
Pre-TasksPart II: Community dinamicsPart I : Community dataTacticalWorkshop OrganizerDomainExpert6.Make presentation of RISCOSS project summary. 7.Explain the RISCOSS analytics platform. 8.Explain the tactical workshop Part I and Part II9.Explain the risk driver selection WS Excel File Excel File: risk driver selection WSTabsTimelinessActivenessCommunity10.Study the use case scenario 11.Assess the use case scenario overall state 12.Determine the level of the risk indicator 13.Study the use case scenario 14.Assess the use case scenario overall state 15.Determine the level of the community risk indicatorPDF File:KPA RISCOSS Analytics [more risk drivers] [not more risk drivers] RISCOSS Analytics Team1.Determine drivers and risk indicators2.Construct Bayesian networks3.Define scenarios4.Identify and contact experts5.Workshops planning and preparation16.Send the scenarios judgementPopulate BN nodes](https://image.slidesharecdn.com/expertmining-compsac-2014-140825162147-phpapp02/85/Expert-mining-compsac-2014-10-320.jpg)
![25
Related Work
Related Work
Delphi method
(QUELCE)
QuantifyingUncertaintyinEarlyCostEstimation[2]
Reliableconsensusofopinionofagroupofexperts[1]
[1]N.DalkeyandO.Helmer,“AnexperimentalapplicationoftheDelphimethodtotheuseofexperts,”.
[2]R.W.Ferguson,D.Goldenson,J.M.McCurley,R.W.Stoddard,andD.Zubrow,“QuantifyingUncertaintyinEarlyLifecycleCostEstimation(QUELCE),”](https://image.slidesharecdn.com/expertmining-compsac-2014-140825162147-phpapp02/85/Expert-mining-compsac-2014-25-320.jpg)
![27
Domain
Expert
Conclusions and further work
Conclusions and further work
Pre-Tasks
Part II:
Community
dinamics
Part I :
Community data
Tactical
Workshop
Organizer
Domain
Expert
6.Make
presentation
of RISCOSS
project
summary.
7.Explain the
RISCOSS
analytics
platform.
8.Explain the
tactical
workshop
Part I and
Part II
9.Explain the
risk driver
selection WS
Excel File
Excel File: risk driver
selection WS
Tabs
Timeliness
Activeness
Community
10.Study the
use case
scenario
11.Assess the
use case
scenario
overall state
12.Determine
the level of
the risk
indicator
13.Study the
use case
scenario
14.Assess the
use case
scenario
overall state
15.Determine
the level of
the
community
risk indicator
PDF File:KPA
RISCOSS
Analytics
[more
risk drivers]
[not more
risk drivers]
RISCOSS
Analytics
Team
1.Determine
drivers and
risk indicators
2.Construct
Bayesian
networks
3.Define
scenarios
4.Identify and
contact
experts
5.Workshops
planning and
preparation
16.Send the
scenarios
judgement
Populate BN
nodes
Domain
Expert SNA
Project Site
Code Version
Repository
Bug Tracker Mailing List IRC
Step-by-step
protocol
Data used to
construct
Bayesian
networks
Future work
Combines opinion
of domain experts
with OSS raw data
Empirical
application
&
lessons](https://image.slidesharecdn.com/expertmining-compsac-2014-140825162147-phpapp02/85/Expert-mining-compsac-2014-27-320.jpg)
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RISCOSS: Gestión del riesgo en proyectos open source (Open Expo Day2015)GESSI UPC El documento presenta el proyecto RISCOSS, el cual desarrolla una metodología y plataforma de software para gestionar los riesgos asociados con la adopción de software de código abierto. La plataforma permite identificar, analizar y mitigar riesgos a través de la recolección y análisis de datos de proyectos y comunidades de código abierto. Se muestra una demostración de las funcionalidades básicas de la plataforma RISCOSS.
Open expo2015 riscoss
Open expo2015 riscossGESSI UPC El documento presenta el proyecto RISCOSS, enfocado en la gestión de riesgos y costos en la adopción de software de código abierto (OSS). Se discuten las motivaciones, los riesgos asociados y la importancia de una gestión efectiva para mitigar impactos negativos en los negocios. Además, se menciona la plataforma RISCOSS como una herramienta para gestionar estos riesgos y facilitar la integración de OSS de manera innovadora.
Oss2015
Oss2015GESSI UPC The document discusses the framework for modeling open source software (OSS) ecosystems, highlighting their significance as business drivers and the increasing complexity and scale of software systems. It emphasizes the need for understanding, evaluating, and monitoring the health and quality of OSS ecosystems through a structured modeling process. Key concepts include collaboration among actors, the evolution of software projects, and the establishment of metrics and evaluation techniques for assessing ecosystem dynamics.
Mobility4 all
Mobility4 allGESSI UPC El documento describe el proyecto Mobility4All, cuyos objetivos son facilitar la movilidad de los ciudadanos con impedimentos, apoyar a los municipios en la detección y supresión de barreras arquitectónicas, y atraer visitantes con impedimentos para su movilidad. El proyecto involucra a municipalidades, centros de investigación y actores tecnológicos en el desarrollo de una plataforma y contenidos para mejorar la accesibilidad urbana y los procesos de gestión municipal.
Er14
Er14GESSI UPC The document discusses the modeling and application of open-source software (OSS) adoption strategies to support organizations in integrating OSS into their business models. It outlines research questions related to OSS projects, activities, and their alignment with organizational goals. Additionally, it presents an ontology for OSS adoption strategies and proposes future work to explore the connections between business models and OSS strategies.
QuESo: a Quality Model for Open Source Software Ecosystems
QuESo: a Quality Model for Open Source Software EcosystemsGESSI UPC This document presents QuESo, a quality model for measuring the quality of open source software ecosystems. It consists of three dimensions: community quality, ecosystem network quality, and platform quality. The authors describe developing the model through a systematic literature review to identify relevant metrics, which were then organized into the quality characteristics and sub-characteristics. Examples of applying the QuESo model for risk analysis and assessing an open source community's health are provided. Future work could involve defining a complete quality assessment process based on the model.
MoDRE 2014 @ RE keynote -- NFR-Aware MDD Processes
MoDRE 2014 @ RE keynote -- NFR-Aware MDD ProcessesGESSI UPC The keynote presentation by Xavier Franch at MODRE 2014 discusses the integration of non-functional requirements (NFRs) in model-driven development (MDD) processes, highlighting the importance of NFRs in software architecture and design decisions. The talk reviews empirical studies and emphasizes the need for MDD processes to be aware of NFRs to improve system quality and performance. Several research directions are suggested, including better representation of NFRs and linking them to architectural decisions.
Quantifying the Impact of OSS Adoption Risks with the help of i* Models
Quantifying the Impact of OSS Adoption Risks with the help of i* ModelsGESSI UPC The document discusses a method for assessing the risks associated with open source software (OSS) adoption using I* models, presented at an I* workshop in June 2014. It emphasizes the importance of understanding the OSS ecosystem, identifying risk drivers, and modeling the interplay between different actors and goals to evaluate potential risks. Future work includes deepening the analysis of connections between indicators, risks, and strategies, as well as integrating model-based and statistical reasoning techniques.
Applying Business Strategy Models in Organizations
Applying Business Strategy Models in OrganizationsGESSI UPC The document outlines a workshop on applying business strategy models in organizations focusing on open source software (OSS). It discusses various strategies for OSS adoption, acquisition, and integration, emphasizing the importance of aligning business models with strategic requirements. The conclusion highlights future work on validating the instantiation operations used in OSS strategies.
Slides refsq'14 ds v1
Slides refsq'14 ds v1GESSI UPC The document proposes using software requirement patterns (SRPs) to improve requirements engineering (RE) by enabling reuse of textual requirements. It defines SRPs as templates that generate natural language requirements from parameters. A PAtterns Based RE framework (PABRE) is designed to facilitate SRP use, addressing research questions about SRP structure/semantics, integration into RE processes, and benefits. The approach involves defining SRPs and a catalog, designing and implementing the PABRE system, and validating the framework and assets. Future work includes improving SRP relationships, evolving PABRE assets, and conducting a validation case study.
A Context Ontology for Service Provisioning and Consumption
A Context Ontology for Service Provisioning and ConsumptionGESSI UPC This document presents the development of a context ontology for service provisioning and consumption. It outlines the ontology development process, including specification, knowledge acquisition from 30 papers, and conceptualization of the knowledge. It also describes a use case scenario and conclusions. The paper aims to provide a unified context ontology and consolidate context information from a service-centric perspective to improve service provisioning and consumption.
Practical Experiences in Designing and Conducting Empirical Studies in Indust...
Practical Experiences in Designing and Conducting Empirical Studies in Indust...GESSI UPC Research paper at Second Intl. Workshop on Conducting Empirical Studies in Industry. CESI 2014 - An ICSE 2014 Workshop (2nd June 2014)
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Assessing Open Source Communities' using Service Oritented Computing concepts
Assessing Open Source Communities' using Service Oritented Computing conceptsGESSI UPC The document discusses assessing the health of open source software communities using concepts from service-oriented computing. It proposes monitoring key health indicators of communities by treating monitoring tools as services that can obtain and apply metrics. This would allow analyzing community data to inform strategies for proactively adapting communities and selecting appropriate open source software. Monitoring could be done actively through embedded sensors or passively through data retrieved from tools.
DB searches vs. snowballing
DB searches vs. snowballingGESSI UPC The document compares two methods for conducting systematic literature reviews: database searches and backward snowballing. It aims to determine the extent to which the two methods find the same papers and draw the same conclusions. The results show the initial and final paper sets from each method are different in number and composition, though some papers overlap. While patterns identified allow for similar conclusions, analyzing only unique papers per method reveals slightly different identified patterns. The conclusion is that the two methods are not highly dependent on each other but combining them generates a more comprehensive analysis, though requires more work. More comparison studies are needed to fairly evaluate the methods.
AK+MDD+NFRs
AK+MDD+NFRsGESSI UPC This document discusses an approach called AK+MDD+NFRs that combines architectural knowledge (AK), model-driven development (MDD), and non-functional requirements (NFRs). It presents an ontology called Arteon with four modules for requirements, reasoning and decision making, architectural elements, and MDD concepts. Architectural decisions are made through either constraint satisfaction or quality-oriented approaches. Ongoing work includes improving the ontology design, populating it with knowledge, validating it with case studies, and providing tool support.
Arteon: Architectural and Technology Ontology
Arteon: Architectural and Technology OntologyGESSI UPC The document provides an overview of the Arteon method and model. It discusses the context, outlines the method which involves requirements analysis, architectural decision making, and increasing knowledge. It then describes the Arteon model which represents requirements, architectural elements, and reasoning in interconnected ontologies. Finally, it discusses ongoing work to improve the ontology design, populate it with knowledge, validate it with case studies, and provide tool support.
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Expert mining compsac-2014
- 1. Expert Mining for Evaluating Risk Indicators ScenariosOscar Franco-Bedoya, Dolors Costal, Soraya Hidalgo, Ron Ben-JacobMonday 21st July 2014
- 2. 2 Background Workshop procedure Generalization of the approach Applications and lessons learned Related work Conclusions and further work Outline
- 3. 3 Background
- 4. 4 Background
- 5. 5 Background Managing risk in open source adoption
- 6. 6 Identification Mitigation methods Management Advanced tools Provides Platform Methods OSS adoption projects To support a In Uses Ecosystem modeling Statistical tools Risk Management i.e. i.e. i.e. Bayesian Networks Social network analysis Expert scenarios assessment e.g. e.g. e.g. Background Risks Systematic protocol uses
- 7. 7 Background Project Site Code Version Repository Bug Tracker Mailing List IRC Ecosystem hubs Project indexes Social Media Twitter Facebook I Raw Data SNA Measures Risk Indicators: • Project • Community • Contextual II Indicators Scenario-based Assessment Domain Expert Business Analysis • Business goals III Business Goals 3-Layered RISCOSS approach Number of downloads Number of event references Centrality Number of open bugs
- 8. 8 Outline Background Workshop procedure Generalization of the approach Applications and lessons learned Related work Conclusions and further work Outline
- 9. 9 The RISCOSS tactical workshop is designed to permit experts to assess risk indicators Workshop procedure
- 10. 10 Tacticalworkshop protocol Workshop procedure Pre-TasksPart II: Community dinamicsPart I : Community dataTacticalWorkshop OrganizerDomainExpert6.Make presentation of RISCOSS project summary. 7.Explain the RISCOSS analytics platform. 8.Explain the tactical workshop Part I and Part II9.Explain the risk driver selection WS Excel File Excel File: risk driver selection WSTabsTimelinessActivenessCommunity10.Study the use case scenario 11.Assess the use case scenario overall state 12.Determine the level of the risk indicator 13.Study the use case scenario 14.Assess the use case scenario overall state 15.Determine the level of the community risk indicatorPDF File:KPA RISCOSS Analytics [more risk drivers] [not more risk drivers] RISCOSS Analytics Team1.Determine drivers and risk indicators2.Construct Bayesian networks3.Define scenarios4.Identify and contact experts5.Workshops planning and preparation16.Send the scenarios judgementPopulate BN nodes
- 11. 11 Pre-Tasks Tactical Workshop Organizer RISCOSS Analytics Team 1.Determine drivers and risk indicators 2.Construct Bayesian networks 3.Define scenarios 4.Identify and contact experts 5.Workshops planning and preparation Correspond to tasks that must be done before conducting the tactical workshop Workshop procedure
- 12. 12 Pre-Tasks Tactical Workshop Organizer RISCOSS Analytics Team 1.Determine drivers and risk indicators 2.Construct Bayesian networks 3.Define scenarios 4.Identify and contact experts 5.Workshops planning and preparation Workshop procedure Risk Driver Forum posts per day Forum messages per thread Mail per day Overall community size Number of developers involved Number of testers (individuals providing feedback) Number of companies using the software Companies supporting the project (adding to code) Risk Indicator Activeness
- 13. 13 Pre-Tasks Tactical Workshop Organizer RISCOSS Analytics Team 1.Determine drivers and risk indicators 2.Construct Bayesian networks 3.Define scenarios 4.Identify and contact experts 5.Workshops planning and preparation Workshop procedure
- 14. 14 Pre-Tasks Tactical Workshop Organizer RISCOSS Analytics Team 1.Determine drivers and risk indicators 2.Construct Bayesian networks 3.Define scenarios 4.Identify and contact experts 5.Workshops planning and preparation Workshop procedure
- 15. 15 Pre-Tasks Tactical Workshop Organizer RISCOSS Analytics Team 1.Determine drivers and risk indicators 2.Construct Bayesian networks 3.Define scenarios 4.Identify and contact experts 5.Workshops planning and preparation Workshop procedure
- 16. 16 The tactical workshops begin with an exposition about the main topics that will be covered Workshop procedure 6.Make presentation of RISCOSS project summary. 7.Explain the RISCOSS analytics platform. 8.Explain the tactical workshop Part I and Part II PDF File:KPA RISCOSS Analytics Tactical Workshop Organizer
- 17. 17 Workshop procedure 9.Explain the risk driver selection WS Excel File Excel File: risk driver selection WS Tabs Timeliness Activeness Community Tactical Workshop Organizer
- 18. 18 Workshop procedure Part I : Community data Domain Expert 10.Study the use case scenario 11.Assess the use case scenario overall state 12.Determine the level of the risk indicator
- 19. 19 Workshop procedure Part II: Community dinamics 13.Study the use case scenario 14.Assess the use case scenario overall state 15.Determine the level of the community risk indicator 16.Send the scenarios judgement Domain Expert
- 20. 20 Outline Outline Background Workshop procedure Generalization of the approach Applications and lessons learned Related work Conclusions and further work
- 21. 21 Generalization of the approach
- 22. 22 Outline Outline Background Workshop procedure Generalization of the approach Applications and lessons learned Related work Conclusions and further work
- 23. 23 Applications and lessons learned Applications and lessons learned We have conducted 10 technical workshops In private and official organizations and academic institutions. The experts were from different countries. France, Israel, Italy, Spain, and Netherlands There are some inconsistencies in the scenarios The scenarios were designed using random number generators While the domain experts are conducting the tactical workshops, The degree of "calibration" of their judgement improves
- 24. 24 Outline Outline Background Workshop procedure Generalization of the approach Applications and lessons learned Related work Conclusions and further work
- 25. 25 Related Work Related Work Delphi method (QUELCE) QuantifyingUncertaintyinEarlyCostEstimation[2] Reliableconsensusofopinionofagroupofexperts[1] [1]N.DalkeyandO.Helmer,“AnexperimentalapplicationoftheDelphimethodtotheuseofexperts,”. [2]R.W.Ferguson,D.Goldenson,J.M.McCurley,R.W.Stoddard,andD.Zubrow,“QuantifyingUncertaintyinEarlyLifecycleCostEstimation(QUELCE),”
- 26. 26 Outline Outline Background Workshop procedure Generalization of the approach Applications and lessons learned Related work Conclusions and further work
- 27. 27 Domain Expert Conclusions and further work Conclusions and further work Pre-Tasks Part II: Community dinamics Part I : Community data Tactical Workshop Organizer Domain Expert 6.Make presentation of RISCOSS project summary. 7.Explain the RISCOSS analytics platform. 8.Explain the tactical workshop Part I and Part II 9.Explain the risk driver selection WS Excel File Excel File: risk driver selection WS Tabs Timeliness Activeness Community 10.Study the use case scenario 11.Assess the use case scenario overall state 12.Determine the level of the risk indicator 13.Study the use case scenario 14.Assess the use case scenario overall state 15.Determine the level of the community risk indicator PDF File:KPA RISCOSS Analytics [more risk drivers] [not more risk drivers] RISCOSS Analytics Team 1.Determine drivers and risk indicators 2.Construct Bayesian networks 3.Define scenarios 4.Identify and contact experts 5.Workshops planning and preparation 16.Send the scenarios judgement Populate BN nodes Domain Expert SNA Project Site Code Version Repository Bug Tracker Mailing List IRC Step-by-step protocol Data used to construct Bayesian networks Future work Combines opinion of domain experts with OSS raw data Empirical application & lessons
- 28. 28 Outline Outline Background Workshop procedure Generalization of the approach Applications and lessons learned Related work Conclusions and further work
- 29. 29 SEeD4FI
- 30. Thanks for your attention Comments and Questions
- 31. 31 SEeD4FI