Abstract Delta lenses are an established mathematical framework for modelling and designing bidirectional model transformations (Bx). Following the recent observations by Fong et al, the paper extends the delta lens framework with a a new ingredient: learning over a parameterized space of model transformations seen as functors. We will define a notion of an asymmetric learning delta lens with amendment (ala-lens), and show how ala-lenses can be organized into a symmetric monoidal (sm) category. We also show that sequential and parallel composition of well-behaved (wb) ala-lenses are also wb so that wb ala-lenses constitute a full sm-subcategory of ala-lenses.

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In the Matlab Simulink environment, systems can be modelled using Simulink block diagrams and Stateflow state charts. While stateful logic is more naturally modelled using Stateflow, in practice complex block diagrams are often used instead, resulting in models that are hard to understand and maintain. In order to improve the maintainability and understandability of large industrial models, this paper presents a strategy for refactoring Simulink block diagrams implementing stateful logic into functionally equivalent Stateflow state charts that more naturally represent the intended behaviour. To bridge the gap between the syntax of block diagrams and state charts, Mealy machines represented by tabular expressions are used as an intermediate representation. The compositional language of block diagrams is used to combine tables modelling individual blocks into a table for the entire block diagram which describes the high level state machine encoded in the Simulink subsystem. A prototype tool that performs the translation from Simulink to Stateflow automatically is discussed.

Abstract Multiple (more than 2) model synchronization is ubiquitous and important for MDE, but its theoretical underpinning gained much less attention than the binary case. Specifically, the latter was extensively studied by the bx community in the framework of algebraic models for update propagation called lenses . We make a step to restore the balance and propose a notion of multiary delta lens. Besides multiarity, our lenses feature reflective updates, when consistency restoration requires some amendment of the update that violated consistency, and a reasonable Put Put law that requires compatibility of update propagation with update composition for a precisely specified restricted class of composable update pairs. We emphasize the importance of various ways of lens composition for practical applications of the framework, and prove several composition results.

Multiple (more than 2) model synchronization is ubiquitous and important for MDE, but its theoretical underpinning gained much less attention than the binary case. Specifically, the latter was extensively studied by the bx community in the framework of algebraic models for update propagation called lenses . Now we make a step to restore the balance and propose a notion of multiary delta lens. Besides multiarity, our lenses feature reflective updates, when consistency restoration requires some amendment of the update that violated consistency. We emphasize the importance of various ways of lens composition for practical applications of the framework, and prove several composition results. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Assurance is a demonstration that a complex system (such as a car or a communication network) possesses an importantproperty, such as safety or security, with a high level of confidence. In contrast to currently dominant approaches to building assurance cases, which are focused on goal structuring and/or logical inference, we propose considering assurance as a model transformation (MT) enterprise: saying that a system possesses an assured property amounts to saying that a particular assurance view of the system comprising the assurance data, satisfies acceptance criteria posed as assurance constraints. While the MT realizing this view is very complex, we show that it can be decomposed into elementary MTs via a hierarchy of refinement steps. The transformations at the bottom level are ordinary MTs that can be executed for data specifying the system, thus providing the assurance data to be checked against the assurance constraints. In this way, assurance amounts to traversing the hierarchy from the top to the bottom and assuring the correctness of each MT in the path. Our approach has a precise mathematical foundation (rooted in process algebra and category theory) --- a necessity if we are to model precisely and then analyze our assurance cases. We discuss the practical applicability of the approach, and argue that it has several advantages over existing approaches.

We propose Example-Driven Modeling (EDM), an approach that systematically uses explicit examples for eliciting, modeling, verifying, and validating complex business knowledge. It emphasizes the use of explicit examples together with abstractions, both for presenting information and when exchanging models. We formulate hypotheses as to why modeling should include explicit examples, discuss how to use the examples, and the required tool support. Building upon results from cognitive psychology and software engineering, we challenge mainstream practices in structural modeling and suggest future directions.

Software development is an evolutionary process. Requirements of a system are often incomplete or inconsistent, and hence need to be extended or modified over time. Customers may demand new services or goals that often lead to changes in the design and implementation of the system. These changes are typically very expensive. Even if only local modifications are needed, manually applying them is time-consuming and and error-prone. Thus, it is essential to assist users in propagating changes across requirements, design, and implementation artifacts. In this paper, we take a model-based approach and provide an automated algorithm for propagating changes between requirements and design models. The key feature of our work is explicating relationships between models at the requirements and design levels. We provide conditions for checking validity of these relationships both syntactically and semantically. We show how our algorithm utilizes the relationships between models at different levels to localize the regions that should be modified. We use the IBM Trade 6 case study to demonstrate our approach.