Model Transformation Framework Research Articles

Digital Transformation of Incumbent Firms: A Business Model Innovation Perspective

The literature argues that a real digital transformation of firms requires holistic changes of the business model. Despite knowledge about this ambitious goal, understanding of how digital business model transformation can be achieved is still very limited. In this article, we explore how firms achieve digital business model transformation. We apply a case study design to investigate how incumbents have changed their respective business model dimensions during digital transformation. Our findings center on interview data and complementary archival records from 15 cases. We present a framework for digital business model transformation along the dimensions of value proposition, value creation, and value capture. Our results emphasize the importance of a preparatory phase in which the strategic course is set. Furthermore, our findings demonstrate that transforming a company's business model is most effective when a single person, namely the Chief Digital Officer, is responsible. Our findings contribute to the business model literature, by providing a more holistic view on how business model innovation can be utilized during digital transformation.

Towards a pattern‐based model transformation framework

AbstractModel‐Driven Development (MDD) is one of the important approaches to develop complex software systems. This approach tries to model a system in high‐abstraction level. Then through applying multiple transformations step by step, the model abstraction level is reduced and finally yields to executable code. As a result, Model transformation (MT) plays a pivotal role on the realization of MDD goals. Due to the increasing complexity of software systems, MTs naturally become more complex. Hence, qualitative technical issues may be overlooked or forgotten in these model transformations. To alleviate these issues in terms of technical debts/code smells in MTs, we can apply MT patterns. A main drawback on applying patterns is that most of them are cataloged in informal language. Additionally, construction of a conceptual framework to help MT designers through applying patterns requires a precise specification of the underlying MT patterns. With a formal basis, this paper is trying to realize the proposed framework. Hence, some of the existing well‐known MT patterns are formalized. Then based on the identified common technical debts/code smells in MTs, a designer can be directed to apply the appropriate patterns and resolve the detected problems iteratively. For the applicability and functionality of the proposed framework, several examples of problematic model transformations in terms of quality flaws were considered and resolved using the appropriate patterns. We consider the Epsilon Transformation Language (ETL) cases of model transformations in this paper, and other similar MT languages could be treated using the same measures and patterns as well.

Towards a pattern-based model transformation framework - formal model of patterns in Alloy

Towards a pattern-based model transformation framework - formal model of patterns in Alloy

A Review of Business Model Transformation in Transportation Business Post Pandemic

This study reviews post-pandemic business models, as demonstrated in transportation business by employing literature study method. Data obtained includes 56 articles published from 2020 to 2022 during Covid-19 pandemic that transform the business model. The results of the study indicate that there are six streams in the literature, namely (1) the impact of Covid-19 on the transportation sector, (2) the built environment for business model transportation, (3) the need for transformation of business models due to new policies, (4) changes in consumer choices and behavior, (5) supply chain management and transportation transformation, and (6) transportation business model planning. The synthesis resulted in a transportation sustainable business model transformation framework involving threat identification, company character, support, built environment, resources and capabilities, design and development, and delivery and evaluation. The transportation business needs to identify aspects of transportation services that need to be improved, adjust internal resources and capabilities, reconfigure the business, and encourage collective agreements to transform the post-pandemic transportation business model. This research contributes to the literature on transform the regular business model. It emphasizes the importance of resources and capabilities to drive business transformation internally and externally in the context of the transportation business.

Towards a pattern-based model transformation framework

Towards a pattern-based model transformation framework

BXtendDSL: A layered framework for bidirectional model transformations combining a declarative and an imperative language

Model-driven software development (MDSD) heavily relies on model transformations. While in a strict forward engineering process unidirectional transformations are used, bidirectional transformations are crucial as soon as roundtrip engineering comes into play. In this paper, we present a hybrid language specifically designed to describe bidirectional model transformations. From a declarative transformation specification code is generated which uses our framework for bidirectional and incremental model transformations. A sophisticated code generation mechanism allows for hooking into the generated transformation code at the imperative level to supply behavior that cannot be expressed declaratively. A thorough evaluation demonstrates conciseness, expressiveness, and scalability of our approach. • Combination of a declarative and imperative language for bidirectional incremental model transformations. • Highly flexible language, allowing for concise transformation specifications. • Provides expressiveness to solve a wide range of transformation problems. • Supports the specification of consistent behavior of forward and backward transformations. • Approach is scalable even for big model sizes.

Correct-by-construction model-based design of reactive streaming software for multi-core embedded systems

We present a model-based design approach toward correct-by-construction implementations of reactive streaming software for multi-core systems. A system’s implementation is derived from a high-level process network model by applying semantics-preserving model transformations. The so-called fixed priority process networks (FPPNs) are programmed independently from the execution platform and combine streaming and reactive control behavior with task parallelism for utilizing multi-core processing. We first define the FPPN sequential execution semantics that specifies precedence constraints between job executions of different tasks. Applications are thus rendered such that for any given test stimuli, a deterministic output response is expected. Furthermore, we define the FPPN real-time semantics based on a timed-automata modeling framework. This is provably a functionally equivalent semantics specifying the real-time execution of FPPNs and enabling runtime managers for scheduling jobs on multi-cores. A model transformation framework has been developed for deriving executable implementations of FPPNs on the BIP (Behavior–Interaction–Priority) runtime environment, ported on multi-core platforms. Schedulability is established by static analysis of the FPPN, and it is guaranteed by construction. Thus, the developers do not need to program low-level real-time OS services (e.g., for task management) and applications are amenable to testing, as opposed to if their outputs would depend on timing behavior. We have successfully ported a guidance-navigation and control application of a satellite system, onto a radiation hardened multi-core platform. Various implementation scenarios for efficiently utilizing HW resources are illustrated, and the test results are discussed.

Model transformation for analyzing dependability of AADL model by using HiP-HOPS

Abstract The Architecture Analysis and Design Language (AADL) has emerged as a potential future standard in aerospace, automobile and avionics industries for model-based development of dependability-critical systems. As AADL is relatively new, some existing analysis methods and tools are not able to accept AADL models. In this paper we show that, by using model transformation techniques, we can automatically transform AADL models into a form that is directly executable by fault-tree-based dependability analysis and optimisation tools. This model transformation opens a path by which AADL models may benefit from automatic synthesis and analysis of fault trees, temporal fault tree analysis, multiple failure mode and effects analysis and model architecture optimisation. In this paper, we present a new model transformation framework. The core of the framework is a novel transformation from a state machine-based error model to a fault-tree model. The framework has been implemented as a plug-in (AADL2HiP-HOPS) for the AADL model development tool OSATE. The plug-in may be used to transform AADL models into a state-of-the-art dependability analysis and optimisation tool: HiP-HOPS. To illustrate the transformation and subsequent HiP-HOPS analysis, an example AADL model is transformed.

Transformation of Alloy Notation into a Semantic Notation

Transformation of a model based on first-order logic to a model that provides semantic notations is helpful necessary during the analysis phase of any proposed software. The semantic notations often guide the designer to develop pseudocode correctly. This study focuses on facilitation of transformation of one formal model, i.e., Alloy into another, i.e., OWL. The proposed approach extends the concept of existing techniques i.e., UML2Alloy and TwoUse to transform Alloy model into OWL. UML2Alloy transforms UML model into Alloy model, whereas TwoUse approach bridges the gap between UML model and OWL model. Alloy2OWL is based on metamodel-based transformation techniques, which help to map source model, i.e., Alloy into target model, i.e., OWL. For the proper explanation of this study, a model transformation framework is presented, which can be applied to other transformation languages. The proposed approach utilizes the Model-Driven Development techniques to deal with the analysis of Alloy model and determines design problems within a specification. In this paper, various challenges are also presented which occur during the transformation of Alloy to OWL.

A local and global tour on MOMoT

Many model transformation scenarios require flexible execution strategies as they should produce models with the highest possible quality. At the same time, transformation problems often span a very large search space with respect to possible transformation results. Recently, different proposals for finding good transformation results without enumerating the complete search space have been proposed by using meta-heuristic search algorithms. However, determining the impact of the different kinds of search algorithms, such as local search or global search, on the transformation results is still an open research topic. In this paper, we present an extension to MOMoT, which is a search-based model transformation tool, for supporting not only global searchers for model transformation orchestrations, but also local ones. This leads to a model transformation framework that allows as the first of its kind multi-objective local and global search. By this, the advantages and disadvantages of global and local search for model transformation orchestration can be evaluated. This is done in a case-study-based evaluation, which compares different performance aspects of the local- and global-search algorithms available in MOMoT. Several interesting conclusions have been drawn from the evaluation: (1) local-search algorithms perform reasonable well with respect to both the search exploration and the execution time for small input models, (2) for bigger input models, their execution time can be similar to those of global-search algorithms, but global-search algorithms tend to outperform local-search algorithms in terms of search exploration, (3) evolutionary algorithms show limitations in situations where single changes of the solution can have a significant impact on the solution’s fitness.

Multi-objective exploration of architectural designs by composition of model transformations

Designing software architectures and optimizing them based on extra-functional properties (EFPs) require to identify appropriate design decisions and to apply them on valid architectural elements. Software designers have to check whether the resulting architecture fulfills the requirements and how it positively improves (possibly conflicting) EFPs. In practice, they apply well-known solutions such as design patterns manually. This is time-consuming, error-prone, and possibly sub-optimal. Well-established approaches automate the search of the design space for an optimal solution. They are based model-driven engineering techniques that formalized design decisions as model transformations and architectural elements as components. Using multi-objective optimizations techniques, they explore the design space by randomly selecting a set of components and applying to them variation operators that include a fixed set of predefined design decisions. In this work, we claim that the design space exploration requires to reason on both architectural components as well as model transformations. More specifically, we focus on possible instantiations of model transformations materialized as the application of model transformation alternatives on a set of architectural components. This approach was prototyped in RAMSES, a model transformation and code generation framework. Experimental results show the capability of our approach (i) to combine evolutionary algorithms and model transformation techniques to explore efficiently a set of architectural alternatives with conflicting EFPs, (ii) to instantiate, and select transformation instances that generate architectures satisfying stringent structural constraints, and (iii) to explore design spaces by chaining more than one transformation. In particular, we evaluated our approach on EFPs, architectures, and design alternatives inspired from the railway industry by chaining model transformations dedicated to implement safety design patterns and software components allocation on a multi-processor hardware platform.

Evaluation of Model Driven Architecture-Based Instruction for Understanding Phase Transitions in Object-Oriented Analysis and Design

Object-Oriented Analysis and Design (OOAD) courses enable students to establish a requirements model of an application, successively transform those requirements into logical design models, and then transform the logical models into physical design models. However, students attending OOAD courses typically encounter difficulties in the transition. Model-Driven Architecture (MDA) provides a model transformation framework for transitioning between OOAD phases. Considering the advantages of MDA in phase transitions, this study proposes that integrating conventional OOAD instruction with the MDA framework and describing transition relations in diagrammatic representations might improve students’ understanding of the transitions. This study used an empirical design that involved using two treatments (MDA-based and conventional instruction) to examine the relevance of MDA-based instruction in the effective understanding of the transitions on the basis of cognitive load theory, the split-attention principle, and theories of representation format. The results indicate that, compared with conventional instruction, MDA-based instruction is more efficient because it improves mental efficiency by reducing extraneous cognitive load. This study can assist educators in understanding the difficulties in learning phase transitions and motivate researchers to develop more effective learning instructions for transitioning between OOAD phases.

Road to a reactive and incremental model transformation platform: three generations of the VIATRA framework

The current release of VIATRA provides open-source tool support for an event-driven, reactive model transformation engine built on top of highly scalable incremental graph queries for models with millions of elements and advanced features such as rule-based design space exploration complex event processing or model obfuscation. However, the history of the VIATRA model transformation framework dates back to over 16 years. Starting as an early academic research prototype as part of the M.Sc project of the the first author it first evolved into a Prolog-based engine followed by a family of open-source projects which by now matured into a component integrated into various industrial and open-source tools and deployed over multiple technologies. This invited paper briefly overviews the evolution of the VIATRA/IncQuery family by highlighting key features and illustrating main transformation concepts along an open case study influenced by an industrial project.

An OCL-Based Framework for Model Transformations

Model transformation is an important building block for model-driven approaches. It puts forward a necessity and a challenge to specify and realize model transformation as well as to ensure the correctness of transformations. This paper proposes an OCL-based framework for model transformations. The formal foundation of the framework is the integration of Triple Graph Grammars and the Object Constraint Language (OCL). The OCL-based transformation framework offers an on-the-fly verification of model transformations and means for transformation quality assurance.

A model transformation framework to increase OCL usability

Abstract The usability of a modeling language has a direct relationship with several factors of models constructed with the modeling language, such as time required and accuracy. Object Constraint Language (OCL) is the most prevalent language to document system constraints that are annotated in the Unified Modeling Language (UML). OCL is reputed as a modeling language with difficult syntax, and prior knowledge of OCL is needed to use the language. These obstacles result in the low usability of OCL. Therefore, the current research proposes a model to automatically transform system constraints formed in English sentences to OCL specifications. The proposed model is based on the Model-Driven Architecture (MDA) approach. The Linear Temporal Logic (LTL) properties of the proposed model are verified by the Maude model checker. To validate the proposed model and compare it with the existing work, the En2OCL (English2OCL) application is developed. This application is tested by three evaluation metrics: precision, recall, and f-measure. The En2OCL application is further compared with the NL2OCLviaSBVR application, which is the existing work on OCL generation from English sentences. The comparison shows a considerable improvement in precision, recall, and f-measure.

Partitioned event graph: formalizing LP-based modelling of parallel discrete-event simulation

Logical process (LP) is a modelling paradigm widely used in parallel discrete-event simulation (PDES). However, effective methods for formalizing LP-based modelling of PDES are lacking. This prevents an unambiguous, platform-independent description of LP-based models. We present a formalism named partitioned event graph (PEG) as a solution. PEG extends classical event graph formalism towards a formal specification for LP-based PDES models. We map between PEG and LP-based models, define the structural operational semantics (SOS) in a timed-labelled transition system, and discuss the Wallclock time-based execution. We propose a PEG-based model transformation framework for PDES, which has three model representation phases and distinguishes amongst four kinds of personnel roles. Finally, we present a domain-specific language (DSL) for the PDES of a Lotka–Volterra system and obtain preliminary parallel simulation results using YinHe Simulation Utilities for Parallel Environment (YHSUPE). The case study shows that the PEG-based framework not only effectively transforms a DSL into the LP paradigm, but will also result in efficient parallel simulation on a specific platform. In summary, by setting out specific characteristics for event scheduling and state space partition in the LP paradigm, PEG provides a formal method for model behaviour analysis and cross-platform model transformation.

Automating building energy system modeling and analysis: An approach based on SysML and model transformations

Abstract A methodology to automate building energy model generation and system analysis is proposed. The contribution of this methodology is to extend the formal model transformation framework toward building energy system modeling, thus enabling efficient and flexible system synthesis through model decomposition and recomposition. It builds on SysML metamodeling and Triple Grammar Graph based model transformation that takes in the descriptive architecture model and outputs the corresponding TRNSYS model in a standardized fashion, thus greatly reducing the potential of heuristic modeling uncertainty. The automation is also extended to the analysis of the synthesized system; thereby human intervention becomes minimized, which expedites decision-makings at various steps of the model-based design exploration. The automation is applied to a special design problem of Model-based Predictive Controls that may contain the heuristic modeling uncertainty in case of custom modeling, and that also requires very frequent system analyses during development. Illustrative examples demonstrate modeling reliability, as well as enhanced modeling and analysis productivity, compared to the manual process. The enhanced productivity even allows extra explorations. If a designer were to create a TRNSYS model by hand, it would most likely be economically feasible to carry out only a few types and rounds of analyses for only a few system configurations at best. With the automated TRNSYS model generation and system analysis, designers can efficiently perform a much larger number of detailed analyses, which would result in an improved exploration of both the design space and the selected alternatives.

Towards a framework for deriving platform-independent model-driven software product lines

Model-driven software product lines (MD-SPLs) are created from domain models which are transformed, merged and composed with reusable core assets, until software products are produced. Model transformation chains (MTCs) must be specified to generate such MD-SPLs. This paper presents a framework for creating platform-independent MD-SPLs; such framework includes a domain specific language (DSL) for platform-independent MTC specification and facilities platform-specific MTC generation of several of the most used model transformation frameworks. The DSL also allows product line architects to compose generation taking the need for model transformation strategy and technology interoperability into account and specifying several types of variability involved in such generation.

Research on Model Transformation Method Oriented to Model Driven ERP System

The model transformation from Computation Independent Model (CIM) to Platform Independent Model (PIM) level is one of the crucial and difficult points in the implementation process of model-driven Enterprise Resource Planning (ERP) system. For achieving the semantic conforming transformation between these two abstract modeling levels in Model Driven Architecture (MDA), a model transformation method based on ontology technology was proposed, which was a semi-automatic and general method. Firstly, the existing problems of model transformation from CIM level to PIM level in current studies were analyzed. Then, a model transformation framework based on ontology was built, the basic concepts relating to ontology were defined, and the whole architecture was described. After that, the transformation method was researched from two parts, the discovering of mapping rules and the occurrence of model transformation, which included the discovering technology of mapping rules based on similarity and the working principles of model transformation generator. Finally, a model transformation example was provided for validating the practicability and feasibility of proposed theories.

Formal Visual Modeling of Real-Time Systems in e-Motions: Two Case Studies

e-Motions is an Eclipse-based visual timed model transformation framework with a Real-Time Maude semantics that supports the usual Maude formal analysis methods, including simulation, reachability analysis, and LTL model checking. e-Motions is characterized by a novel and powerful set of constructs for expressing timed behaviors. In this paper we illustrate the use of these constructs --- and thereby implicitly investigate their suitability to define real-time systems in an intuitive way --- to define and formally analyze two prototypical and very different real-time systems: (i) a simple round trip time protocol for computing the time it takes a message to travel from one node to another, and back; and (ii) the EDF scheduling algorithm.