The increasing complexity of modern systems leads to an increasing amount of artifacts that are used along the model-based software and systems development lifecycle. This also includes model transformations, which serve for mapping models between representations, e.g., for verification and validation purposes. Model repositories manage this variety of artifacts and promote reusability, but should also enable the bundling of compatible artifacts. Therefore, model transformations should be reused and arranged into transformation chains to support more complex transformation scenarios. The resulting transformation should correspond to the user’s interest in terms of quality criteria such as model coverage, transformation coverage, and number of transformation steps, thus assembling such chains becomes a multi-objective problem. A novel multi-objective approach for exploring possible transformation chains residing in model repositories is presented. MOMoT, a model-driven optimization framework, is leveraged to explore the transformation space spanned by the repository. For demonstration, three differently populated repositories are considered. We have extended MOMoT with an exhaustive, multi-objective search that explores the entire model transformation space defined by graph transformation rules, allowing all possible transformation chains to be considered as solution. Accordingly, the optimal solutions were identified in the demonstration cases with negligible computation time. The approach assists modelers when there are multiple chains for transforming an input model to a specified output model to consider. Our evaluation shows that the approach elicits all legitimate transformation chains, thus enabling the modelers to consider trade-offs in view of multiple criteria selection.

Abstract Low‐code development platforms (LCDPs) aim to simplify software systems' development by providing easy‐to‐use graphical interfaces and drag‐and‐drop facilities. The system behaviors are defined through available data handling and workflow mechanisms enabling the specification of business processes from users that do not have strong programming skills. However, the number of LCDPs has grown significantly over the last few years. Consequently, it is not easy for inexpert users to understand their differences, especially in terms of provided modeling constructs. In this article, we analyze and compare eight low‐code development platforms by focusing on their capabilities for specifying business processes. The analysis exploits business process modeling and notation (BPMN) as a reference modeling language. Thus, the core elements of BPMN are leveraged to analyze the workflow mechanisms provided by each of the analyzed LCDP. The article explains different types of process flows and data handling means of the different LCDPs aiming to give potential users objective elements that can be used to make educated decisions when selecting LCDPs.

Low-code development platforms (LCDPs) are easy to use visual environments that are being increasingly introduced and promoted by major IT players to permit citizen developers to build their software systems even if they lack a programming background. Understanding and evaluating the LCDP to be employed for the particular problem at hand are difficult tasks mainly because decision-makers have to choose among hundreds of heterogeneous platforms, which are difficult to evaluate without dedicated support. Thus, a detailed classification is needed to elaborate on the existing low-code platforms and to help users find out the most appropriate platforms based on their requirements.In this paper, a technical survey of different LCDPs is presented by relying on a proposed conceptual comparative framework. In particular, by analyzing eight representative LCDPs, a corresponding set of features have been identified to distil the functionalities and the services that each considered platform can support. The final aim is facilitating the understanding and the comparison of the low-code platforms that can best accommodate given user requirements.