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Interactive metamodel/model co-evolution using unsupervised learning and multi-objective search

Published: 16 October 2020 Publication History

Abstract

Metamodels evolve even more frequently than programming languages. This evolution process may result in a large number of instance models that are no longer conforming to the revised metamodel. On the one hand, the manual adaptation of models after the metamodels' evolution can be tedious, error-prone, and time-consuming. On the other hand, the automated co-evolution of metamodels/models is challenging, especially when new semantics is introduced to the metamodels. While some interactive techniques have been proposed, designers still need to explore a large number of possible revised models, which makes the interaction time-consuming. In this paper, we propose an interactive multi-objective approach that dynamically adapts and interactively suggests edit operations to designers based on three objectives: minimizing the deviation with the initial model, the number of non-conformities with the revised metamodel and the number of changes. The proposed approach proposes to the user few regions of interest by clustering the set of recommended co-evolution solutions of the multi-objective search. Thus, users can quickly select their preferred cluster and give feedback on a smaller number of solutions by eliminating similar ones. This feedback is then used to guide the search for the next iterations if the user is still not satisfied. We evaluated our approach on a set of metamodel/model co-evolution case studies and compared it to existing fully automated and interactive co-evolution techniques.

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  • (2024)"Don’t Touch my Model!" Towards Managing Model History and Versions during Metamodel EvolutionProceedings of the 2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results10.1145/3639476.3639758(77-81)Online publication date: 14-Apr-2024
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  1. Interactive metamodel/model co-evolution using unsupervised learning and multi-objective search

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    cover image ACM Conferences
    MODELS '20: Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems
    October 2020
    406 pages
    ISBN:9781450370196
    DOI:10.1145/3365438
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 16 October 2020

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    1. interactive multi-objective search
    2. metamodel/model co-evolution
    3. search based software engineering

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    View all
    • (2024)"Don’t Touch my Model!" Towards Managing Model History and Versions during Metamodel EvolutionProceedings of the 2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results10.1145/3639476.3639758(77-81)Online publication date: 14-Apr-2024
    • (2024)Supporting reusable model migration with EdeltaJournal of Systems and Software10.1016/j.jss.2024.112012212:COnline publication date: 1-Jun-2024
    • (2024)Interactive search-based Product Line Architecture designAutomated Software Engineering10.1007/s10515-024-00457-631:2Online publication date: 9-Jul-2024
    • (2023)Automated Extraction of Grammar Optimization Rule Configurations for Metamodel-Grammar Co-evolutionProceedings of the 16th ACM SIGPLAN International Conference on Software Language Engineering10.1145/3623476.3623525(84-96)Online publication date: 23-Oct-2023
    • (2023)Studying the Influence and Distribution of the Human Effort in a Hybrid Fitness Function for Search-Based Model-Driven EngineeringIEEE Transactions on Software Engineering10.1109/TSE.2023.332973049:12(5189-5202)Online publication date: 1-Dec-2023
    • (2023)A modeling assistant to manage technical debt in coupled evolutionInformation and Software Technology10.1016/j.infsof.2022.107146156:COnline publication date: 1-Apr-2023
    • (2022)Validating an Interactive Ranking Operator for NSGA-II to Support the Optimization of Software Engineering ProblemsProceedings of the XXXVI Brazilian Symposium on Software Engineering10.1145/3555228.3555232(337-346)Online publication date: 5-Oct-2022

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