Incremental Consistency Checking of Dynamic Constraints

Groher, Iris; Reder, Alexander; Egyed, Alexander

doi:10.1007/978-3-642-12029-9_15

Cited by 34 publications

(28 citation statements)

References 12 publications

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“…In [12] and [9], we have shown that the Model/Analyzer is capable of validating constraints instantly, even for large industrial models of over 100,000 model elements. Moreover, it was demonstrated that adding constraints (or removing them) is handled efficiently.…”

Section: Preliminary Performance Resultsmentioning

confidence: 99%

“…Consistency Checking After updating the set of constraints imposed by the metamodel, standard consistency checkings mechanisms (e.g., [8,9]) can be used to detect inconsistencies. While the typical scenario is that an unchanged model becomes inconsistent after metamodel evolution, it is also possible that a previously inconsistent model becomes consistent without any adaptations.…”

Section: Constraint Managementmentioning

confidence: 99%

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Co-evolution of metamodels and models through consistent change propagation

Demuth

Riedl-Ehrenleitner

Lopez-Herrejon

et al. 2016

Journal of Systems and Software

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Abstract. In Model-Driven Engineering (MDE), metamodels and domain-specific languages are key artifacts as they are used to define syntax and semantics of domain models. However, metamodels are evolving over time, requiring existing domain models to be co-evolved. Though approaches have been proposed for performing such co-evolution automatically, those approaches typically support only specific metamodel changes. In this paper, we present a vision of co-evolution between metamodels and models through consistent change propagation. The approach addressed co-evolution issues without being limited to specific metamodels or evolution scenarios. It relies on incremental management of metamodel-based constraints that are used to detect co-evolution failures (i.e., inconsistencies between metamodel and model). After failure detection, the approach automatically generates suggestions for correction (i.e., repairs for inconsistencies). Preliminary validation results are promising as they indicate that the approach computes correct suggestions for model adaptations, and that it scales and can be applied live without interrupting tool users.

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Section: Preliminary Performance Resultsmentioning

confidence: 99%

Section: Constraint Managementmentioning

confidence: 99%

Co-evolution of metamodels and models through consistent change propagation

Demuth

Riedl-Ehrenleitner

Lopez-Herrejon

et al. 2016

Journal of Systems and Software

Self Cite

View full text Add to dashboard Cite

show abstract

“…In [6], [7] also transformation approach is followed. Groher et al [8] makes use of description logic in order to find discrepancies between state chart and sequence diagrams. Campbell et al [9] explored a model named SPIN for consistency checking in UML.…”

Section: Related Workmentioning

confidence: 99%

A Model Driven Framework for Automatic Detection and Tracking Inconsistencies

Rao¹,

Kanth²,

Ramesh³

2016

JSW

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Software design model inconsistencies precipitate into flaws in system that can be avoided at the time of design of the system. Recent contributions in the software engineering domain confirmed this fact clearly. Obstructions in software development and delivery can lead to economic and time-to-market attributes of the software. The consequences of model inconsistencies will have ripple effect in three areas such as cost, development time and delivery. Though UML provides unified and common notations across the globe, the developers may use the models inappropriately leading to model inconsistencies. Many researches came into existence to handle model inconstancies. However, a comprehensive, flexible and extensible framework that caters to the needs of developers with diverse tool usage and skill set is desired. Towards this end, in our previous work, we proposed a framework named Extensible Real Time Software Design Inconsistency Checker (XRTSDIC) for checking software design inconsistencies. The framework was made flexible with placeholders to support different modeling tools, rule detectors and visualizations. In this paper we focus on providing more features for all placeholders to realize a truly flexible and extensible design inconsistency checker. This improved framework and the implemented prototype can help software engineers to build more consistent software design models that can avoid cost and budget overruns as the application can provide early detection of inconstancies. Moreover, the application can support certain degree of tolerance for inconsistencies and help software engineers to switch between UML tools, consistency checkers and visualization mechanisms. The empirical evaluation shows that our framework is flexible and reveals significant performance improvement over other state-of-the-art inconsistency checkers in terms of accuracy, speed and scalability.

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“…Thus, a constraint is violated if its corresponding view is not empty. Other techniques follow a different approach aimed at incrementally checking the OCL constraints [5,6,7]. That is, assuming that no OCL constraint is violated for the current data, they determine which OCL constraints should be checked, and for which data, after some update is applied to the information system.…”

Section: Fig 2 Ocl Constraints For the Simplified Uml Class Diagrammentioning

confidence: 99%

Incremental Checking of OCL Constraints with Aggregates Through SQL

Oriol

Teniente

2015

Conceptual Modeling

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Abstract. Valid states of data are those satisfying a set of constraints. Therefore, efficiently checking whether some constraint has been violated after a data update is an important problem in data management. We tackle this problem by incrementally checking OCL constraint violations by means of SQL queries. Given an OCL constraint, we obtain a set of SQL queries that returns the data that violates the constraint. In this way, we can check the validity of the data by checking the emptiness of these queries. The queries that we obtain are incremental since they are only executed when some relevant data update may violate the constraint, and they only examine the data related to the update.

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Incremental Consistency Checking of Dynamic Constraints

Cited by 34 publications

References 12 publications

Co-evolution of metamodels and models through consistent change propagation

Co-evolution of metamodels and models through consistent change propagation

A Model Driven Framework for Automatic Detection and Tracking Inconsistencies

Incremental Checking of OCL Constraints with Aggregates Through SQL

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