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Feature Location in Models (FLiMEA)
Universidad San Jorge
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FLiMEA
Why? How? What? Where? FLiMEA Feature Location Problem
Search Space: Model Ranking of Model Fragments Solution: Model Fragments Feature Description
Feature Location in Models (FLiMEA) Universidad San Jorge 1 FLiMEA - - PowerPoint PPT Presentation
Feature Location in Models (FLiMEA) Universidad San Jorge 1 FLiMEA - - PowerPoint PPT Presentation
REVAMP 2 Feature Location in Models (FLiMEA) Universidad San Jorge 1 FLiMEA REVAMP 2 What? Why? Where? How? Feature Location Problem Feature Description Ranking of Model Fragments Solution: Model Fragments Search Space: Model FLiMEA 2
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Why is Feature Location important?
FLiMEA
Why? How? What? Where?
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FLiMEA
Why? How? What? Where? UML Class Diagram BPMN Entity Relationship Grafcet Textual modeling
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FLiMEA
Why? How? What? Where?
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FLiMEA
Why? How? What? Where?
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Why? How? What? Where?
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Learning to Rank is the name given to a family of Machine Learning algorithms, which automatically address ranking tasks. Individual Individual Individual Individual Individual Individuals Ranking Why? How? What? Where?
FLiMEA
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Individual Individual Individual Individual Individual Individuals Ranking Classifier Why? How? What? Where?
FLiMEA
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Individual Individual Individual Individual Individual Feature Vectors Individuals Ranking Classifier Why? How? What? Where?
FLiMEA
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Why? How? What? Where?
FLiMEA
Ideal house Under construction house
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Individual Individual Individual Individual Model Fragment Feature Vectors Model Fragments Ranking Encoding Classifier Why? How? What? Where?
FLiMEA
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Why? How? What? Where?
FLiMEA
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Why? How? What? Where?
FLiMEA
Model Fragment Evolutionary Algorithm Learning to Rank FLiMEA
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Why? How? What? Where?
FLiMEA
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Why? How? What? Where?
FLiMEA
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Why? How? What? Where?
FLiMEA
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Demo
Why? How? What? Where?
FLiMEA
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Induction Hobs of B/S/H/
(produced under the Bosch, Siemens, Balay, Neff, Gaggenau brands, among others)
Industrial experiences
Rolling stock of CAF
(Trains, Trams, High-speed, and Underground)
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Publications
▪ JSS 2018, Improving feature location in long-living model-based product families designed with sustainability goals. ▪ MODELS 2018, Evolutionary Algorithm for Bug Location in the Reconfigurations of Models at Runtime. ▪ MODELS 2018, Measures to report the Location Problem of Model Fragment Location. ▪ CAiSE 2018, Exploring New Directions in Traceability Link Recovery in Models. ▪ GPCE 2017, Analyzing the impact of natural language processing over feature location in models. ▪ ER 2017, Ontological evolutionary encoding to bridge machine learning and conceptual models: approach and industrial evaluation. ▪ ER Forum 2017, On the Influence of Models-to Natural-Language Transformation among Requirements and Conceptual Models. ▪ REVE 2017, Towards Feature Location in Models through a Learning to Rank Approach.
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More info
Font, Jaime; Arcega, Lorena; Haugen, Øystein; Cetina, Carlos; Achieving Feature Location in Families of Models through the use of Search-Based Software
- Engineering. IEEE Transactions on Evolutionary computation. 2018
Marcén, Ana Cristina; Pérez, Francisca; Cetina, Carlos; Ontological Evolutionary Encoding to Bridge Machine Learning and Conceptual Models: Approach and Industrial Evaluation. 36th International Conference on Conceptual Modeling. 2017 Pérez, Francisca; Marcén, Ana Cristina; Lapeña, Raúl; Cetina, Carlos; Introducing Collaboration for Locating Features in Models: Approach and Industrial Evaluation. 25th International Conference on Cooperative Information Systems. 2017
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Contact us
Universidad San Jorge: Ana C. Marcén acmarcen@usj.es Carlos Cetina ccetina@usj.es Jaime Font jfont@usj.es Research Group Website: REVAMP Web Site: http://svit.usj.es http://revamp-project.eu/
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