Towards Memory-Efficient Validation of Large XMI Models

TY - GEN

T1 - Towards Memory-Efficient Validation of Large XMI Models

AU - Jahanbin, Sorour

AU - Kolovos, Dimitris

AU - Gerasimou, Simos

N1 - Funding Information: ACKNOWLEDGMENT This research is supported by the Lowcomote Training Network, which has received funding from the European Union’s Horizon 2020 Research and InnovationProgram under the Marie Skłodowska-Curiegrant agreement no 813884. © 2023 IEEE. This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.

PY - 2023/12/22

Y1 - 2023/12/22

N2 - Model validation is a common activity in model-driven engineering, where a model is checked against a set of consistency rules (also referred to as constraints) to assess whether it has desirable properties further to those that can be expressed by the metamodel that it conforms to (e.g. to check that all states in a state machine are reachable or that no classes in an object-oriented model are involved in circular inheritance relationships). Such constraints can be written in general-purpose (e.g. Java) or in task-specific validation languages such as the Object Constraint Language (OCL) or the Epsilon Validation Language (EVL). To check a model that is serialised in the OMG-standard XMI format against a set of constraints, the current state of practice requires loading the entire model into memory first. This can be problematic in cases where loading the model into memory requires more memory (heap space) than is available in the host machine, and is sub-optimal when carrying out distributed model validation over a number of machines. In this paper, we present an approach that uses static analysis to split sets of model validation constraints into sub-groups that operate on smaller subsets of the model. Combined with existing XMI partial loading capabilities, the proposed approach makes it possible to check larger XMI - based models on a single machine and to potentially improve efficiency when checking models in a distributed setting.

AB - Model validation is a common activity in model-driven engineering, where a model is checked against a set of consistency rules (also referred to as constraints) to assess whether it has desirable properties further to those that can be expressed by the metamodel that it conforms to (e.g. to check that all states in a state machine are reachable or that no classes in an object-oriented model are involved in circular inheritance relationships). Such constraints can be written in general-purpose (e.g. Java) or in task-specific validation languages such as the Object Constraint Language (OCL) or the Epsilon Validation Language (EVL). To check a model that is serialised in the OMG-standard XMI format against a set of constraints, the current state of practice requires loading the entire model into memory first. This can be problematic in cases where loading the model into memory requires more memory (heap space) than is available in the host machine, and is sub-optimal when carrying out distributed model validation over a number of machines. In this paper, we present an approach that uses static analysis to split sets of model validation constraints into sub-groups that operate on smaller subsets of the model. Combined with existing XMI partial loading capabilities, the proposed approach makes it possible to check larger XMI - based models on a single machine and to potentially improve efficiency when checking models in a distributed setting.

KW - file-based model

KW - memory management

KW - model validation

KW - model-driven engineering

KW - partial loading

KW - XMI model

UR - http://www.scopus.com/inward/record.url?scp=85182391331&partnerID=8YFLogxK

U2 - 10.1109/MODELS-C59198.2023.00053

DO - 10.1109/MODELS-C59198.2023.00053

M3 - Conference contribution

AN - SCOPUS:85182391331

T3 - Proceedings - 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2023

SP - 241

EP - 250

BT - Proceedings - 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2023

Y2 - 1 October 2023 through 6 October 2023

ER -