Model Transformation Research Articles

Russia and Turkey in the early 21st century: transformation of bilateral interaction models

In the article, the author undertakes an examination of three distinct periods in the history of Russian-Turkish relations. From a chronological perspective, these periods encompass the 2000s, the 2010s, and the first half of the 2020s. By the end of the first quarter of the 21st century, Russia and Turkey had begun to accord a higher level of priority to their relations with each other in a number of areas, including diplomatic interaction at the global and regional levels, trade and economic relations, energy and military-technical cooperation. This situation starkly contrasts with the late 1990s, when Turkey demonstrated a tendency to align with the “collective West” in a manner driven by both inertia and ideology. The author posits that Russian-Turkish relations have undergone a dynamic transformation over the past quarter of a century, while each of the periods under consideration exhibiting a unique constellation of complementarity and competition. These two aspects defined the respective models of bilateral relations in each period. Existing research focuses mainly on various discrete aspects of the relationship between the two countries – be it diplomatic interaction, energy, or issues of intertwined or competing interests in specific hotspots and regions such as Syria, Libya, the Middle East, Central Asia, and the Caucasus. At the same time, a comprehensive analysis of the driving forces behind the transformation of Russia-Turkey relations is still lacking in academic publications on Turkey. In order to present such an analysis, this article draws on a number of important primary sources, including official documents of Russian and Turkish state agencies and structures involved in the implementation of foreign policy, national statistics, publications of news agencies, and leading media.

SNHG15 is involved in the progression of atherosclerosis through targeted regulation of miR-370-3p and bioinformatics analysis

IntroductionThis study aimed to explore the expression of SNHG15 in atherosclerotic population and further evaluate the regulatory mechanism of SNHG15 in AS.Material and methodsqRT-PCR was used to detect the level of SNHG15 in serum samples. An in vitro cell model was constructed using 50 µg/ml ox-LDL-induced VSMCs. Transwell, CCK-8 assay and ELISA were used to detect the migration, proliferation, phenotypic transformation, and inflammatory reaction of the cell model. The interaction between SNHG15 and miR-370-3p was verified by the luciferase reporter gene. Pearson analysis was used to assess the correlation between SNHG15 and miR-370-3p. The target genes of miR-370-3p and their functions were evaluated by bioinformatics analysis.ResultsThe expression of SNHG15 in the AS group and ox-LDL-induced VSMCs group were upregulated (p < 0.001), while miR-370-3p was decreased (p < 0.001). In vitro studies showed that inhibition of SNHG15 can obviously weaken the proliferation, migration, phenotypic transformation, and inflammation of VSMCs induced by ox-LDL (p < 0.01). Bioinformatics and luciferase reporter gene confirmed that miR-370-3p was the downstream target gene of SNHG15. Pearson correlation coefficient revealed that miR-370-3p was negatively regulated by SNHG15 (r = –0.6998, p < 0.001). Bioinformatics analysis indicated that miR-370-3p had 160 potential target genes, whose functions were mainly related to cell cycle and cell adhesion, and were mainly concentrated in the MAPK signaling pathway. Further analysis showed that the downstream target gene of miR-370-3p was FOXO1.ConclusionsSNHG15 mediated cell proliferation, migration, phenotypic transformation, and inflammation response via inhibiting miR-370-3p in ox-LDL-induced VSMCs.

E-commerce and the Transformation of Offline Retail in China: Based on the Perspective of Sales Model Transformation

This paper focuses on the in-depth exploration of how traditional offline retail has been impacted by e-commerce to a certain extent in the context of the wave of e-commerce sweeping the world, and how to flexibly cope with this great change, survive and stand out in such competitive challenges, not only quickly integrate into and adapt to the new market environment, but also stabilize its position and continue to develop in the highly competitive consumer market The strategic path of the exhibition is to compare the purchase channels of various categories of e-commerce transactions in the past 5 years, e-commerce sales, e-commerce purchases, wholesale and retail end goods inventory The analysis of offline retail and other data and the use of SWOT analysis to comprehensively analyze the future development mode of China's offline retail and the importance of e-commerce and digital transformation to China's offline retail, so as to obtain targeted information from the government Suggestions are given at the three levels of the industry and the company itself, and the problems and challenges that may exist and need to be further solved and improved in the transformation of the traditional offline retail industry are also explained.

From Traditional to Digital: The Evolution of Business Models in Hospitality Through Platforms

The hospitality business model has undergone profound changes influenced by successive waves of technological advances and platforms. This paper explores how different waves of technologies and platforms are shaping the evolution of the hospitality business model. Employing a systematic literature review, this research analyzes how platform innovation has driven significant shifts in the industry. The analysis yielded four key findings. Firstly, the incorporation of digital technologies resulted in a radical transformation of conventional business models, prompting substantial alterations in marketing strategies, distribution processes, and consumer behavior patterns. Secondly, the industry has undergone five significant technological revolutions, evolving from steam-powered transportation to the integration of artificial intelligence (AI) and the Internet of Things (IoT), thereby driving a shift towards innovation-centric business models. Thirdly, the advent of digital platforms, most notably online travel agencies (OTAs), posed a challenge to traditional hospitality models by introducing personalized experiences and disrupting established market norms. While digital platforms offer advantages such as enhanced convenience and customization, they also present challenges, including intensified competition and declining profit margins. Nonetheless, technological advancements such as AI, virtual reality (VR), and augmented reality (AR) present a potential avenue for redefining value propositions and enhancing customer experiences. Fourth, the future of the hospitality business model is poised for further disruption, influenced by the emergence of new virtual platforms and services. This could potentially result in a reshaping of the industry’s value chain and value proposition.

Законодавчо-правове регулювання платформної зайнятості у контексті соціальної стійкості держави

The article considers the issue of maintaining the state social resilience through the prism of the development of digital platforms and the emergence of the digital labor market as a new reality for the information-network economy. Attention is focused on the fact that the transformation of traditional models of social and labor relations prompts the search for ways and means of the regulation of non-standard forms of employment, in particular platform employment related to work on digital (online-, Internet-) platforms. The authors carry out an analytical assessment of international approaches to regulating the activities of digital platforms and recommendations for improving working conditions for platform employment. Shown various legal peculiarities and the variety of national practices of labor regulation in the platform economy in different countries. The article presents variants of terminology on the subject, and the most common areas of application of legislation and regulations regarding digital platforms and employees of such platforms in the ILO’s member states. Revealed the directions of domestic legislative and legal regulation of certain forms of non-standard employment, such as remote work, work with the use of flexible working time, labor relations with non-fixed working time. It is noted that a separate case of such forms of non-standard employment can be considered platform employment, the specifics of whose regulation are not taken into account in Ukraine’s legislation. The authors summarize the recommendations on the regulation of platform economy and platform employment based on modern international approaches and practices. The main legally regulated aspects of platform employment are identified, being among the most important of them the issues of concluding labor contracts, extending social protection standards to platform employees, transparency in the use of algorithms, and guaranteeing the right to appeal decisions made by artificial intelligence. It is emphasized that special attention should be paid to the creation of a tripartite committee in Ukraine for the preparation by the parties of national social partnership of consolidated approaches to the regulation of platform employment. Proposed various guidelines for legal regulation of platform employment, which would minimize its precarization potential and contribute to social resilience in post-war Ukraine.

RESEARCH STATUS, HOTSPOTS AND EVOLUTİON İN THE FİELD OF ONLİNE MUSİC EDUCATİON: A BİBLİOMETRİC REVİEW

ABSTRACT In the contemporary era of swift informational advancement, the rapid progression of digital technology has become especially significant, profoundly reshaping numerous fields. Globally, the demand for personalized learning, an emerging educational model, is increasing day by day, while the discussion and pursuit of unified educational standards are also gradually strengthening. This parallel pursuit of educational diversity and standardization reflects society's expectations and demands for high-quality education. Against this backdrop, we have witnessed the transformation of educational models, particularly the widely recognized and valued importance of collaborative learning and the sharing of educational resources. This trend is not only evident in traditional educational practices but also significantly manifested and developed in the field of online education. In this wave of educational change, the online music education sector has attracted widespread attention with its unique charm and potential. Music education, as an artistic form rich in creativity and emotional expression, has provided learners with brand-new learning experiences and possibilities through its online trend. However, despite the rapid development of online music education, existing research lags, particularly in the quantitative and empirical analysis of bibliometric indicators such as influential authors, popular topics, and evolutionary trends. To fill this gap, our research utilizes abundant data from the globally authoritative Web of Science (WOS) database. Through systematic literature review and analysis, we aim to reveal the core content and characteristics of the online music education field. In this process, we employ VOSviewer, a powerful analytical tool, which helps us gain a deep understanding of multiple dimensions within this field, including the distribution of authors, geographical contributions, key journals, co-occurring keywords, and co-cited references. Through this series of in-depth analyses, we not only clearly depict the current status of the online music education field but also reveal its frontier hotspots and future evolution trends. The insights from this study aim to provide scholars and educators in this field with a comprehensive and multidimensional perspective, serving as a strong reference and guidance for their future research and work.

Nonlinear Optimal and Multi-Loop Flatness-Basedcontrol of Omnidirectional 3-Wheel Mobile Robots

In this article, the control problem for omnidirectional 3-wheel autonomous mobile robots is solved with the use of (i) a nonlinear optimal control method (ii) a flatness-based control approach which is implemented in successive loops. To apply method (i) that is nonlinear optimal control, the dynamic model of the omnidirectional 3-wheel autonomous mobile robots undergoes approximate linearization at each sampling instant with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrix. The linearization point is defined by the present value of the system's state vector and by the last sampled value of the control inputs vector. To compute the feedback gains of the optimal controller an algebraic Riccati equation is repetitively solved at each time-step of the control algorithm. The global stability properties of the nonlinear optimal control method are proven through Lyapunov analysis. To implement control method (ii), that is flatness-based control in successive loops, the state-space model of the omnidirectional 3-wheel autonomous mobile robot is separated into chained subsystems, which are connected in cascading loops. Each one of these subsystems can be viewed independently as a differentially flat system and control about it can be performed with inversion of its dynamics as in the case of input-output linearized flat systems. The state variables of the preceding (i-th) subsystem become virtual control inputs for the subsequent (i+1-th) subsystem. In turn, exogenous control inputs are applied to the last subsystem. The whole control method is implemented in successive loops and its global stability properties are also proven through Lyapunov stability analysis. The proposed method achieves trajectory tracking and autonomous navigation for the omnidirectional 3-wheel autonomous mobile robots without the need of diffeomorphisms and complicated state-space model transformations.

Consensus of second-order multi-agent systems based on PIDD-like control protocol with time delay

This paper concentrates on investigating the consensus for general second-order linear multiagent systems subjected to time-varying delay. Initially, a novel PIDD-like consensus control protocol with time-varying delay is designed, which includes information on position and its integration, as well as velocity and its differentiation. Subsequently, based upon model transformation, the consensus problem is transformed into the asymptotic stability of the error system. Through constructing of a novel augmented vector Lyapunov-Krasovskii functional, including delay-product terms and multiple integral terms, and then by adopting auxiliary-function-based integral inequalities and the delay-dependent-matrix-based reciprocally convex inequality to address the derivative of the constructed functional, the less conservative consensus conditions for multi-agent systems are obtained. Additionally, numerical simulations are given to demonstrate that the presented consensus conditions not only ensure the consensus of position and velocity states but also exhibit better dynamic performance.

Transformation of the business ecosystem model into energy enterprise’s strategy

Transformation of the business ecosystem model into energy enterprise’s strategy

Anti-Sway Adaptive Fast Terminal Sliding Mode Control Based on the Finite-Time State Observer for the Overhead Crane System

This work proposes an adaptive rapid terminal SMC (sliding mode control) approach based on the FFTSO (fast finite-time state observer) for overhead crane trajectory tracking and anti-swing control in the presence of external disturbances and parameter uncertainty. First, the system state observation under the constraint of unknown system parameters is accomplished by designing the FFTSO based on finite-time theory. Next, a parameter-adaptive fast terminal SMC is created for an overhead crane based on the model transformation. This technique can still monitor the intended trajectory and reduce payload swing even in cases when the payload mass and wire rope length are uncertain. Next, the Lyapunov theorem is used to demonstrate the stability of the overhead crane system’s positioning and anti-swing angle control mechanism. Lastly, the platform experiments confirm that the suggested closed-loop system control technique is successful.

Відкрита наука в сучасному дослідницькому просторі

The article comprehensively examines theoretical and practical aspects of open science development in the modern research space. The evolution of the open science concept has been analyzed. It has been determined that the modern understanding of open science is based on the principles of transparency, collaboration, and inclusivity, which are implemented through open access to publications, research data, and methodologies. The role of leading international organizations in the development of open science has been investigated. In particular, SPARC's activities in overcoming inequalities in scientific communication, Science Europe's contribution to the formation of research data management standards, and Coalition S's impact on the transformation of scientific publishing models have been analyzed. It has been established that these organizations play a key role in shaping open science policies, developing infrastructure, and implementing new models of scientific communication. Special attention has been paid to the development of open science in Ukraine in the context of European integration and the formation of national open access infrastructure. The main directions of development have been analyzed, including the creation of a network of institutional repositories, development of open access journals, legislative support, and international cooperation. Ukraine's high performance in open data has been noted, indicating significant progress in implementing public information transparency policies. Based on the analysis, key components of modern open science have been identified, including open research data complying with FAIR principles, open research methods, open peer review of scientific works, and digital infrastructure. The main challenges of open science development have been revealed, particularly financial aspects of open access publishing, technical issues of data standardization and storage, overcoming cultural barriers, and the need to change established practices. The prospects for further development of open science have been substantiated, which are associated with improving technological infrastructure, implementing effective mechanisms for evaluating scientific activities, and creating incentives for adherence to open science principles

Transformation of the Ukrainian agrarian model in the context of accession to the EU

Abstract The article determines the strategy for the development and transformation of Ukraine’s agricultural system in the process of accession to the EU. This article analyzes the most common contemporary political systems and business models of agriculture in the world. On this basis, the current model of the agricultural system of Ukraine was compared with the most common models in European and American countries. The scope of the analysis concerned the historical, economic, and organizational conditions of individual models, their properties, and development prospects in the context of the needs of Ukrainian agriculture. For this purpose, SWOT analysis was used, among others, which allowed the most credible scenarios for the development of Ukraine’s agricultural sector to be verified. The conducted research allowed not only to systematize the literature in the area of agricultural business models but also to formulate the author’s vision for agricultural business models and agrarian system models.

Transformation of the Constitutional Model of Public Formations in the Republic of Belarus

The transformation of the constitutional model of public formations in the conditions of formation and development of the Republic of Belarus is considered as a formal legal objectification of the relevant principles and categorical and conceptual apparatus within the framework of the dynamics of constitutional regulation caused by socio-political and other factors, it provides for a transition from the perception of public formations as an element of the party-state mechanism to the recognition of their independence and functional diversity with the presence of political priority in the intended purpose. It is noted that at the present stage, the constitutional model of public formations in the Republic of Belarus is being transformed within the framework of the development of the constitutional foundations of democracy and civil society, the consolidation of the ideology of the Belarusian state as a constitutional dominant, the revision of the purpose and differentiation. Proposals are being made to develop the relevant constitutional legislation in the Republic of Belarus.

Participatory Method to Business Model Innovation for Students

The past few years have been a period of intense transformation. Pandemics, innovative technology like chatbots, and the ever-evolving needs of society serve as a powerful illustration of the world's constant evolution. Equipping students with business model innovation (BMI) skills across disciplines is crucial as it fosters their ability to innovate not just products and processes, but entire businesses, which is essential in an everchanging environment. Furthermore, integrating remote participative modelling (PM) into the curriculum is essential as it enhances students’ online collaboration skills, vital in today's modern team dynamics. A previous study at a research-intensive university explored the usability of online platforms during BMI within a Business Engineering module focused on entrepreneurship and innovation. MURAL, a virtual whiteboard software application, was used in this study to facilitate remote PM sessions utilising the Business Model Canvas (BMC). While this study found that MURAL is easy-to-use within this specific context, a key limitation emerged. The built-in BMC template within MURAL was found to be insufficient for guiding students through a systematic transformation of a traditional business model into a new iteration. To address this limitation, this current study focuses on enhancing a well-established Business Model Development Tool (BMDT), the BMC, within the context of undergraduate engineering education. We propose a method, called EDU-BMI, specifically designed to support students during PM sessions focused on BMI activities within the MURAL platform. Drawing inspiration from PICO, an educational personal ideation companion, EDU-BMI incorporates features that address educational, social, and motivational aspects. The method is embedded within MURAL and validated through a two-group participant study. Observations of the modelling sessions were used to gather valuable insights into the method's effectiveness and will inform future teaching practices. Integrating EDU-BMI into MURAL has the potential to improve the effectiveness of remote PM sessions for students engaged in BMI activities. Accessibility for modellers will also be ensured by leveraging a free, online tool like MURAL. Future research will focus on evaluating the method in an undergraduate engineering education context, refining EDU-BMI based on the feedback received from participants.

Mission-Oriented Research and Theory of Change: Driving Australia’s Transition to a Circular Economy

AbstractAustralia’s linear economic system hinders the collective pursuit of sustainability, equity, and well-being. As demands for housing, food, energy, transportation, and goods escalate, transitioning to a circular economy becomes imperative. Such a transition necessitates a transformation in business and governance models, as well as cultural shifts, to foster sustainable material flows. The proposed change will likely unfold in five phases: envisioning a circular economy future, evaluating options and trade-offs, initiating local actions, amplifying national efforts, and solidifying global agreements. This shift will occur within the context of significant technical, environmental, social, and economic megatrends, and each phase is likely to overlap with the next, with some phases occurring concomitantly and ongoing. It will reshape socio-technical systems and social practices that fulfil our essential needs. Moreover, this transformation process is inherently circular, characterised by continuous cycles of learning, adaptation, and risk management.

From single-objective to multi-objective reinforcement learning-based model transformation

AbstractModel-driven optimization allows to directly apply domain-specific modeling languages to define models which are subsequently optimized by applying a predefined set of model transformation rules. Objectives guide the optimization processes which can range from one single objective formulation resulting in one single solution to a set of objectives that necessitates the identification of a Pareto-optimal set of solutions. In recent years, a multitude of reinforcement learning approaches has been proposed that support both optimization cases and competitive results for various problem instances have been reported. However, their application to the field of model-driven optimization has not gained much attention yet, especially when compared to the extensive application of meta-heuristic search approaches such as genetic algorithms. Thus, there is a lack of knowledge about the applicability and performance of reinforcement learning for model-driven optimization. We therefore present in this paper a general framework for applying reinforcement learning to model-driven optimization problems. In particular, we show how a catalog of different reinforcement learning algorithms can be integrated with existing model-driven optimization approaches that use a transformation rule application encoding. We exemplify this integration by presenting a dedicated reinforcement learning extension for MOMoT. We build on this tool support and investigate several case studies for validating the applicability of reinforcement learning for model-driven optimization and compare the performance against a genetic algorithm. The results show clear advantages of using RL for single-objective problems, especially for cases where the transformation steps are highly dependent on each other. For multi-objective problems, the results are more diverse and case-specific, which further motivates the usage of model-driven optimization to utilize different approaches to find the best solutions.

Incremental model transformations with triple graph grammars for multi-version models and multi-version pattern matching

AbstractLike conventional software projects, projects in model-driven software engineering require adequate management of multiple versions of development artifacts, importantly allowing living with temporary inconsistencies. In previous work, we have introduced multi-version models for model-driven software engineering, which allow checking well-formedness and finding merge conflicts for multiple versions of the same model at once. However, situations where different models are linked via automatic model transformations also have to be handled for multi-version models. In this paper, we propose a technique for jointly handling the transformation of multiple versions of a source model into corresponding versions of a target model. This enables the use of a more compact representation that may afford improved execution time of both the transformation and further analysis. Our approach is based on the well-known formalism of triple graph grammars and the aforementioned encoding of model version histories called multi-version models. In addition to batch transformation of an entire history, the technique covers incremental synchronization of changes in the framework of multi-version models. Our solution is complemented by a dedicated pattern matching technique for multi-version models. We show the correctness of our approach with respect to the standard semantics of triple graph grammars and conduct an empirical evaluation to investigate the performance of our technique regarding execution time and memory consumption. Our results indicate that the proposed solution affords lower memory consumption and may improve execution time for batch transformation of large version histories, but can also come with computational overhead in unfavorable cases.

Influence of Blood Sampling Service Process Reengineering on Medical Services Supply: Quasi-Experimental Study.

Tertiary hospitals in China are confronted with significant challenges due to limited spatial capacity and workforce constraints, leading to saturated allocation of medical resources and restricted growth in medical service provision. The incorporation of digital health into medical service process reengineering (MSPR) marks a pivotal transformation and restructuring of conventional health service delivery models. Specifically, the application of MSPR to blood sampling services processes reengineering (BSSPR) holds promise for substantially enhancing the efficiency and quality of medical services through streamlining and optimizing these procedures. However, the comprehensive impact of BSSPR has been infrequently quantified in existing research. This study aims to investigate the influence of BSSPR on the efficiency and quality of medical services and to elucidate the key informative technological support points underpinning BSSPR. Data were collected from both the new and old laboratory information systems from August 1, 2019, to December 31, 2021. A combination of statistical description, chi-square test, and t test was used to compare check-in time and waiting time of outpatients before and after the implementation of BSSPR. An interrupted time-series design was used to analyze the impact of BSSPR on medical service efficiency and quality, enabling the control of confounding variables, including changes in medical human resources and both long- and short-term temporal trends. BSSPR had an impact on the efficiency and quality of medical services. Notably, there was a significant increase in the number of patients receiving blood sampling services, with a daily service volume increase of ~150 individuals (P=.04). The average waiting time for patients decreased substantially from 29 (SD 36) to 11 (SD 11) minutes, indicating a marked improvement in patient experience. During the peak period, the number of patients receiving blood sampling services per working hour statistically increased from 9.56 to 16.77 (P<.001). The interrupted time-series model results demonstrated a reduction in patients' waiting time by an average of 26.1 (SD 3.8; 95% CI -33.64 to -18.57) minutes. Although there was an initial decline in the number of outpatients admitted following BSSPR implementation, an upward trend was observed over time (β=1.13, 95% CI 0.91-1.36). BSSPR implementation for outpatients not only reduced waiting time and improved patients' experience but also augmented the hospital's capacity to provide medical services. This study's findings offer valuable insights into the potential advantages of BSSPR and underscore the significance of harnessing digital technologies to optimize medical service processes. This research serves as a foundational basis and provides scientific support for the promotion and application of BSSPR in other health care contexts. By continuing to explore and refine the integration of digital technologies in health care, we can further enhance patient outcomes and elevate the overall quality of medical services.

Novelty Classification Model Use in Reinforcement Learning for Cervical Cancer.

Cervical cancer significantly impacts global health, where early detection is piv- otal for improving patient outcomes. This study aims to enhance the accuracy of cervical cancer diagnosis by addressing class imbalance through a novel hybrid deep learning model. The proposed model, RL-CancerNet, integrates EfficientNetV2 and Vision Transformers (ViTs) within a Reinforcement Learning (RL) framework. EfficientNetV2 extracts local features from cervical cytology images to capture fine-grained details, while ViTs analyze these features to recognize global dependencies across image patches. To address class imbalance, an RL agent dynamically adjusts the focus towards minority classes, thus reducing the common bias towards majority classes in medical image classification. Additionally, a Supporter Module incorporating Conv3D and BiLSTM layers with an attention mechanism enhances contextual learning. RL-CancerNet was evaluated on the benchmark cervical cytology datasets Herlev and SipaKMeD, achieving an exceptional accuracy of 99.7%. This performance surpasses several state-of-the-art models, demonstrating the model's effectiveness in identifying subtle diagnostic features in complex backgrounds. The integration of CNNs, ViTs, and RL into RL-CancerNet significantly improves the diagnostic accuracy of cervical cancer screenings. This model not only advances the field of automated medical screening but also provides a scalable framework adaptable to other medical imaging tasks, potentially enhancing diagnostic processes across various medical domains.

Empowering model repair: a rule-based approach to graph repair without side effects—extended version

Working with models can lead to inconsistencies, e.g., due to erroneous or contradictory actions during concurrent modeling processes. Modern modeling environments typically tolerate inconsistencies and support their detection. However, at a later stage of development, models are expected to be consistent, meaning their inconsistencies should be considered and resolved. The process of resolving model inconsistencies is commonly referred to as model repair. Our approach to model repair is semi-automatic in the sense that the repair tool computes appropriate repair plans and the modeler decides which path to take. The speciality of our approach is that the repair process can register any small improvement in the model. This allows the interaction with the user to be optimized, resulting in an approach with a high level of automation on the one hand and flexible configuration options on the other. The approach focuses on providing repair plans that do not have side effects, i.e., the computed repair plans do not inadvertently introduce a new inconsistency of already repaired constraints into the model. Since models often have a graph-like structure, we present our approach to model repair based on graphs. Our approach is completely formal—we use the algebraic graph transformation approach to prove its correctness. We also present a prototype implementation of our repair approach based on the Eclipse Modeling Framework and Henshin, a model transformation engine based on graph transformation, to perform the actual model repair. A first performance evaluation shows that graphs with up to 1000 nodes can be repaired in about 10 s.