Abstract
Models are not static entities: they evolve over time due to changes. Changes may inadvertently and surprisingly violate constraints imposed. Therefore, the models need to be monitored for compliance. On the one hand, in traditional design-time applications, new and evolving requirements impose changes on a model over time. These changes may accidentally break design rules. Further, the growing complexity of the models may need to be tracked for manageability. On the other hand, newer applications use models at runtime; building runtime abstractions that are used to control a system. Adopters of these approaches will need to query the history of the system to check if the models evolved as expected, or to find out the reasons for a particular behavior. Changes over models at runtime are more frequent than changes over design models. To cover these demands, we argue that a flexible and scalable approach for querying the history of the models is needed to study the evolution and for compliance sake. This paper presents a set of extensions to a model query language inspired in the Object Constraint Language (the Epsilon Object Language) for traversing the history of a model, and for making temporal assertions that will allow the elicitation of historic information. As querying long histories may be costly, the paper presents an approach that annotates versions of interest as they are observed, in order to provide efficient recalls in possible future queries. The approach has been implemented in a model indexing tool, and is demonstrated through a case study from the autonomous and self-adaptive systems domain.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems, MODELS 2019 |
| Editors | Marouane Kessentini, Tao Yue, Tao Yue, Alexander Pretschner, Sebastian Voss, Loli Burgueno, Loli Burgueno |
| Publisher | IEEE |
| Pages | 194-204 |
| Number of pages | 11 |
| ISBN (Electronic) | 9781728125350, 978-1-7281-2536-7 |
| ISBN (Print) | 978-1-7281-2537-4 |
| DOIs | |
| Publication status | Published - 21 Nov 2019 |
| Event | 22nd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2019 - Munich, Germany Duration: 15 Sep 2019 → 20 Sep 2019 |
Conference
| Conference | 22nd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2019 |
|---|---|
| Country | Germany |
| City | Munich |
| Period | 15/09/19 → 20/09/19 |
Fingerprint
Keywords
- model querying
- model versioning
- model-indexing
- scalable model-driven engineering
- temporal graph databases
Cite this
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Querying and Annotating Model Histories with Time-Aware Patterns. / García-Domínguez, Antonio; Bencomo, Nelly; Parra-Ullauri, Juan Marcelo; García-Paucar, Luis Hernán.
Proceedings - 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems, MODELS 2019. ed. / Marouane Kessentini; Tao Yue; Tao Yue; Alexander Pretschner; Sebastian Voss; Loli Burgueno; Loli Burgueno. IEEE, 2019. p. 194-204 8906985.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Querying and Annotating Model Histories with Time-Aware Patterns
AU - García-Domínguez, Antonio
AU - Bencomo, Nelly
AU - Parra-Ullauri, Juan Marcelo
AU - García-Paucar, Luis Hernán
PY - 2019/11/21
Y1 - 2019/11/21
N2 - Models are not static entities: they evolve over time due to changes. Changes may inadvertently and surprisingly violate constraints imposed. Therefore, the models need to be monitored for compliance. On the one hand, in traditional design-time applications, new and evolving requirements impose changes on a model over time. These changes may accidentally break design rules. Further, the growing complexity of the models may need to be tracked for manageability. On the other hand, newer applications use models at runtime; building runtime abstractions that are used to control a system. Adopters of these approaches will need to query the history of the system to check if the models evolved as expected, or to find out the reasons for a particular behavior. Changes over models at runtime are more frequent than changes over design models. To cover these demands, we argue that a flexible and scalable approach for querying the history of the models is needed to study the evolution and for compliance sake. This paper presents a set of extensions to a model query language inspired in the Object Constraint Language (the Epsilon Object Language) for traversing the history of a model, and for making temporal assertions that will allow the elicitation of historic information. As querying long histories may be costly, the paper presents an approach that annotates versions of interest as they are observed, in order to provide efficient recalls in possible future queries. The approach has been implemented in a model indexing tool, and is demonstrated through a case study from the autonomous and self-adaptive systems domain.
AB - Models are not static entities: they evolve over time due to changes. Changes may inadvertently and surprisingly violate constraints imposed. Therefore, the models need to be monitored for compliance. On the one hand, in traditional design-time applications, new and evolving requirements impose changes on a model over time. These changes may accidentally break design rules. Further, the growing complexity of the models may need to be tracked for manageability. On the other hand, newer applications use models at runtime; building runtime abstractions that are used to control a system. Adopters of these approaches will need to query the history of the system to check if the models evolved as expected, or to find out the reasons for a particular behavior. Changes over models at runtime are more frequent than changes over design models. To cover these demands, we argue that a flexible and scalable approach for querying the history of the models is needed to study the evolution and for compliance sake. This paper presents a set of extensions to a model query language inspired in the Object Constraint Language (the Epsilon Object Language) for traversing the history of a model, and for making temporal assertions that will allow the elicitation of historic information. As querying long histories may be costly, the paper presents an approach that annotates versions of interest as they are observed, in order to provide efficient recalls in possible future queries. The approach has been implemented in a model indexing tool, and is demonstrated through a case study from the autonomous and self-adaptive systems domain.
KW - model querying
KW - model versioning
KW - model-indexing
KW - scalable model-driven engineering
KW - temporal graph databases
UR - http://www.scopus.com/inward/record.url?scp=85076091008&partnerID=8YFLogxK
UR - https://ieeexplore.ieee.org/document/8906985
U2 - 10.1109/MODELS.2019.000-2
DO - 10.1109/MODELS.2019.000-2
M3 - Conference contribution
AN - SCOPUS:85076091008
SN - 978-1-7281-2537-4
SP - 194
EP - 204
BT - Proceedings - 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems, MODELS 2019
A2 - Kessentini, Marouane
A2 - Yue, Tao
A2 - Yue, Tao
A2 - Pretschner, Alexander
A2 - Voss, Sebastian
A2 - Burgueno, Loli
A2 - Burgueno, Loli
PB - IEEE
ER -