TY - JOUR
T1 - SAMOS - A framework for model analytics and management
AU - Babur, Önder
AU - Cleophas, Loek
AU - van den Brand, Mark
N1 - Publisher Copyright:
© 2022 The Author(s)
PY - 2022/11/1
Y1 - 2022/11/1
N2 - The increased popularity and adoption of model-* engineering paradigms, such as model-driven and model-based engineering, leads to an increase in the number of models, metamodels, model transformations and other related artifacts. This calls for automated techniques to analyze large collections of those artifacts to manage model-* ecosystems. SAMOS is a framework to address this challenge: it treats model-* artifacts as data, and applies various techniques—ranging from information retrieval to machine learning—to analyze those artifacts in a holistic, scalable and efficient way. Such analyses can help to understand and manage those ecosystems.
AB - The increased popularity and adoption of model-* engineering paradigms, such as model-driven and model-based engineering, leads to an increase in the number of models, metamodels, model transformations and other related artifacts. This calls for automated techniques to analyze large collections of those artifacts to manage model-* ecosystems. SAMOS is a framework to address this challenge: it treats model-* artifacts as data, and applies various techniques—ranging from information retrieval to machine learning—to analyze those artifacts in a holistic, scalable and efficient way. Such analyses can help to understand and manage those ecosystems.
KW - Information retrieval
KW - Machine learning
KW - Model analytics
KW - Model-driven engineering
KW - Software ecosystems
UR - http://www.scopus.com/inward/record.url?scp=85139020175&partnerID=8YFLogxK
U2 - 10.1016/j.scico.2022.102877
DO - 10.1016/j.scico.2022.102877
M3 - Article
AN - SCOPUS:85139020175
SN - 0167-6423
VL - 223
JO - Science of Computer Programming
JF - Science of Computer Programming
M1 - 102877
ER -