In Model-Driven Engineering (MDE), the Unified Modeling Language (UML) is often combined with the Object Constraint Language (OCL) to express constraints on models. While these constraints are typically used for validation, certain tasks-such as model search, completion, repair, or exploration–require the automatic generation of models that satisfy them. Due to the combinatorial nature of these tasks, even small models can lead to computationally complex problems. Constraint Programming (CP) offers a powerful paradigm for modeling and solving such combinatorial challenges, notably through the use of global constraints, which enable concise models supported by efficient algorithms. Although previous approaches have tackled model search using tools like Alloy or ATLc, they often rely on simplified subsets or avoid the use of global constraints. In this paper, we extend the ATLc approach by leveraging CP to the expressiveness and coverage of UML/OCL. We introduce a CP model for representing UML instances and evaluating queries, along with global constraint formulations for UML collection types (Sequence, Bag, Set, OrderedSet) and their corresponding OCL type casting operations (asSequence, asBag, asSet and asOrderedSet). Finally we provide an implementation allowing us to test our model for this subset of OCL and compare with related work.

Abstract To cope with the increased complexity of systems, models are used to capture what is considered the essence of a system. Such models are typically represented as a graph, which is queried to gain insight into the modelled system. Often, the results of these queries need to be adjusted according to updated requirements and are therefore a subject of maintenance activities. It is thus necessary to support writing model queries with adequate languages. However, in order to stay meaningful, the analysis results need to be refreshed as soon as the underlying models change. Therefore, a good execution speed is mandatory in order to cope with frequent model changes. In this paper, we propose a benchmark to assess model query technologies in the presence of model change sequences in the domain of social media. We present solutions to this benchmark in a variety of 11 different tools and compare them with respect to explicitness of incrementalization, asymptotic complexity and performance.

Models have been shown to be useful during virtually all stages of the software lifecycle. They can be reverse engineered from existing artifacts, or created as part of a system's execution, but in many cases models are created by designers from informal specifications. In the latter case, such design models are typically used as means of communication between designers, and developers. They can also in some cases be validated by simulation over test cases, or even by formal verification. However, most existing model simulation or verification approaches require relatively consistent and complete models, whereas design models often start small, incomplete, and inconsistent. Moreover, few design models actually reach the stage where they can be simulated, and even fewer the stage where they can be formally verified. In order to address this issue, we propose a partial modeling approach that makes it possible to animate incomplete and inconsistent models. This approach makes it possible to incrementally improve testable models, and can also help designers reach the stage where their models can be formally verified. A proof-of-concept tool called AnimUML has been created in order to provide means to evaluate the approach on several examples. They are all executable, and some can even undergo model-checking.