Enterprise Modeling: A Multi-perspective Tool-Supported Approach

General-purpose modeling languages are inadequate to model and visualize business processes precisely. An enterprise has its own vocabulary for modeling processes and its specific tasks may have attached data that define the tasks precisely. We propose using Domain Specific Modeling (DSM) languages to model business processes, such that an enterprise can define its own DSM language(s) capturing its vocabulary and data requirement. We suggest using UML profiles and UML activity diagrams as the semantic base for these DSM languages and present tools that are able to create a DSM language and tool support for a given domain. One tool, called ADSpecializer, can generate a UML profile and its tool support of a given application domain. The other tool, ADModeler, is used to create UML activity diagrams within such a domain-specific UML profile. The two tools enable an enterprise to efficiently define and utilize their own DSM language.

Compared to General Purpose Modeling Languages (GPMLs), Domain Specific Modeling Languages (DSMLs) have brought increasing expressivity and conciseness through the use of concepts and notations, which are customized by the characteristics of a specific problem domain. However, the creation of completely new languages can significantly increase software development costs. An alternative approach to creating new DSMLs refers to a customization of existing modeling languages. The DSML creation process through a customization of existing languages is a special case of Language Embedding. The embedding provides customization of an inherited infrastructure to a given domain. This paper elaborates a Domain-Specific Modeling environment for embedding an arbitrary DSML into an arbitrary GPML. The environment enables uniform development of DSMLs in the form of a lightweight extension of existing modeling languages.

The International Workshop on Non-functional System Properties in Domain Specific Modeling Languages (NFPinDSML) series traditionally takes place as part of the Satellite Events of the ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS). Traditionally, NFPinDSML gathers researchers and practitioners interested in the estimation and evaluation of system quality and their integration in Domain Specific Modeling Languages and Model Driven Engineering in general. This paper is the summary of the fourth NFPinDSML workshop which was affiliated with MODELS 2012.

The development and use of Domain Specific Languages emerged as a way to cope with complex problems using concepts closer to the problem domain. By leveraging the principles proposed by Model-Driven Development (MDD), like the separation of concerns and the use of model transformations, this approach became popular and caused the emergence of a variety of languages, known as Domain Specific Modeling Languages (DSMLs). Moreover, the use of DSMLs with graphical notations abstracts even more the problem domain, either by using extensions of UML or directly using metamodeling languages. The definition and use of DSMLs is only possible through specific tools, known as languages workbenches. This paper discusses the analysis and comparison of three of these tools (namely Papyrus, Enterprise Architect and Sirius) that were used to create the XIS-Mobile language, a non-trivial DSML defined as a UML profile for modeling mobile applications in a platform-independent way. These tools were evaluated considering a set of key criteria (namely learnability, usability, graphical completeness, validation support, transformation support, evolvability and interoperability) which show their suitability to develop non-trivial languages.

The paper is devoted to the convergence of critical and non-critical IT in the area of Business Analysis and Requirements Engineering. We consider Domain Specific Modelling (DSM) and Domain Specific Language (DSL) as promising points to improve Requirements Engineering maturity and quality in a safety-critical and security-critical domain. The paper presents a DSM-based procedure of knowledge management that can be implemented in a software engineering company to support the reuse of domain knowledge and technical solutions. Afterward, we select Gherkin language as a sample of DSL-based requirements elicitation, analysis, documentation, and validation in a frame of Behavior Driven Development. To provide a DSM&DSL-based Requirements Engineering technique we analyzed Gherkin's applicability for different kinds and levels of critical requirements.

ADELFE is a French acronym that means “Toolkit for Designing Software with Emergent Functionalities” (“Atelier de DEveloppement de Logiciels à Fonctionnalité Emergente” in French). ADELFE methodology is dedicated to applications characterized by openness and the need of the system adaptation to an environment. Its main goal is to help and guide any designer during the development of an Adaptive Multi-agent System (AMAS). An AMAS is characterized by the following points: it is plunged into an environment and composed of interdependent agents, each agent carries out a partial function and the agents, organization during runtime makes the system realize an emergent function. Actually, an agent is locally cooperative, i.e. it is able to recognize cooperation failures called Non-cooperative Situations (NCS, which could be related to exceptions in classical programs) and treat them.ADELFE includes five Work Definitions that were initially inspired from the Rational Unified Process (RUP) and gathers 21 activities, producing or refining 12 work products. These products are aggregating modelling diagrams or structured or free text. ADELFE, which is a Model-Driven (model-centred) development method, is not hardly dependent on Domain Specific Modelling Languages (DSML) but currently the recommendation is to use UML2 for general activities and to use AMASML (AMAS Modelling Language) and SpeADL (Species-based Modelling Language) for specific activities appearing in Analysis, Design or Implementation phases.KeywordsAdaptive Multi-agent Systems (AMAS)Domain-specific Modeling Languages (DSML)AMAS ApproachAMAS TheoryManagement Studies ConferenceThese 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.

MDA requires the ability to understand different languages such as general purpose languages, domain specific languages, modeling languages or programming languages. An underlying principle of MDA for integrating semantically in a unified and interoperable way such languages is using metamodeling techniques.

Within the world of automation the trend of model-driven object oriented (oo) engineering has brought up fundamental questions about the applicability of these programming paradigms for Programmable Logic Controller (PLC) software. The authors present the results of previously conducted experiments on the usability of the classic procedural paradigm (IEC 61131-3) in machine and plant automation compared to model based approaches for PLC programming, in particular Unified Modeling Language (UML) and domain specific modeling languages. Extrapolating these experiments, we propose a way of enhancing usability evaluations by two means: First we present an improved modeling tool. Second, in order to determine the complexity of the tasks required to develop a PLC-program and to create constant boundary conditions for experimental studies, we propose using Hierarchical Task Analysis (HTA) on both model-driven oo and the state of the art programming approach, concerning typical scenarios. Finally the results of our work are discussed.

Educational games are serious games that specifically used for education yet it is fun to play. There are numbers of domain specific modeling languages for educational games focus in various aspect and theories of learning. By having domain specific modeling language which applies a visual diagramming language, it helps in represent design ideas and logic. This paper analyzes existing modelling languages to assess the coverage of strategy genre and transfer learning concepts. The results show that existing modelling languages covers important strategy genre concepts but cover very little of the transfer learning concepts. The authors conclude that the existing modelling languages can be used to model small strategy games but will have trouble to scale to large strategy games, and will not be able to model games that guarantee students learning.

Among model comprehension tools, model slicers are tools that extract a subset of model elements, for a specific purpose. Model slicers provide a mechanism to isolate and focus on parts of the model, thereby improving the overall analysis process. However, existing slicers are dedicated to a specific modeling language. This is an issue when we observe that new domain specific modeling languages, for which we want slicing abilities, are created almost on a daily basis. This paper proposes the Kompren language to model and generate model slicers for any DSL (e.g. modeling for software development or for civil engineering) and for different purposes (e.g. monitoring and model comprehension). We detail the semantics of the Kompren language and of the model slicer generator. This provides a set of expected properties about the slices that are extracted by the different forms of the slicer. Then we illustrate these different forms of slicers on case studies from various domains.

Critical systems are present in our daily life and affect many aspects providing essential support to several human activities; they are employed in several application domains, providing support to economic activities, transportation, communication, health-care. Such systems must meet strict non-functional requirements, including dependability requirements, and should be able to cope with competitive market needs. Their criticality implies the necessity to meet several requirements, often dictated by international standards, whose fulfillment must be demonstrated in order to achieve necessary certifications. Quantitative evaluations are hence needed to assess and demonstrate compliance with target requirements, since design phases of the lifecycle. For this purpose modeling approaches have been investigated during the years; their aim is to have a of the overall system which allows to assess and demonstrate these properties. It is commonly known that the adoption of formal models in industry, although if strongly recommended when not mandatory, is slowed down by difficulties dictated both by the complexity of the models (which reflects the complexity of the systems) and by the need to have skilled staff in the usage of formal languages. For this reason, also if the academic research trends have focused on complex modeling approaches and techniques, formal models are not so used in industries: in particular only combinatorial models are widely adopted, thanks to their intuitive representation. The great simplifications introduced by combinatorial models lead to approximated results, hence system designers do not trust in them. In the last years the need of a model engineering is noticed: there is the necessity to define appropriate methodologies and processes to support development activities of complex models, aiming at improving the quality/cost ratio. In this way three main research trends have been introduced: formal models generation, multiformalism, and compositional approaches. This thesis aims at defining a methodology for quantitative analysis of critical system that can integrate Model-Based evaluations, conducted by using formal models, with Model-Driven Engineering (MDE) paradigms, taking advantage of the actual research trends. More in detail, according to such approach, critical systems properties can be assessed starting from high level models expressed in proper languages (usually called Domain Specific Modeling Languages - DSMLs), and defining automatic transformation chains, able to generate formal models. The methodology is implementable into cost-effective processes in order to reduce time-to-market specifically during verification stages of critical system development lifecycles. Such objective will be achieved by both improving usability and re-usability of typical Model-Driven artifacts. The adoption of this methodology for railway system dependability analysis may lead to an estimated costs reduction of approximately 30%. The usage of a high-level central language significantly decreases also the training time of new analysts, as they only need to learn the DSML usage (properly developed for the application domain). This thesis defines also two high-level modeling languages: the first, CIP_VAM, has been defined to vulnerability aspects of physical infrastructures, while the second, DAM-Rail, allows the dependability modeling in railway domain. Another important contribution of this thesis is given in the definition of new methods and formal operators: in detail a reference architecture for performability and Quality of Service evaluation is defined, as well as the formal concept of Model Template is introduced (to enable reuse). At last two techniques which deals with scalability are addressed: stub and reduced models. Even if the focus is on quantitative evaluation, the proposed methodology is useful also for the complete design (based on centralized informations), hence it is possible to extend it for automatic generation of documents and, more generally, of all those artifacts which support system development. The proposed approach has been applied with different goals to case studies coming from three different domains: railway systems, conferencing systems, and sensor network. These systems have different and complementary properties in terms of number of involved components, scalability, etc. Produced models are described, and obtained results are shown and commented.

The subject of the research is machine learning models and methods for generating legal contracts with limited resources and performance evaluation benchmarks. The goal of the work is to analyse approaches of domain-specific Large Language Models development and to find the optimal method of creating independent specialized systems that can generate contracts in different languages and legal systems. The article addresses the following tasks: identification of existing companies and solutions in this area, exploring approaches to create texts in natural language, analysis of evaluation and comparison methods of such systems, inspecting limitations and shortcomings of existing solutions and approaches, finding the optimal method of developing systems with limited resources. The following results were obtained: approaches of natural language generation and their features were investigated; the "Transformer" architecture was defined as a modern standard in the field of text information generation; different model types which are based on this architecture were considered; data sources for training were analysed; methods of adapting models in specialized areas were considered; model evaluating benchmarks for various tasks were reviewed; shortcomings of the existing specialized language models and the incompleteness of existing benchmarks for contract generation task evaluation were revealed. As a result of the analytical experiment, it was determined that the Retrieval-Augmented Generation method is the most optimal for solving the given task under the given conditions. The conducted experiment and its results can be used as a basis for further research of domain-specific language models development with limited resources. Conclusions: the article provides an overview of natural language generation methods using modern machine learning techniques, considers their advantages and disadvantages for small companies and scientific institutions that have limited resources. The work examinates a specialized legal domain and the problem of contract generation and determines the most optimal method to solve it.

Software development processes are collaborative in nature. Neglecting the key role of end-users leads to software unlikely to satisfy their needs. This collaboration becomes specially important when creating Domain-Specific Modeling Languages (DSMLs), which are (modeling) languages specifically designed to carry out the tasks of a particular domain. While end-users are actually the experts of the domain for which a DSML is developed, their participation in the DSML specification process is still rather limited nowadays. In this paper, we propose a more community-aware language development process by enabling the active participation of all community members (both developers and end-users of the DSML) from the very beginning. Our proposal is based on a DSML itself, called Collaboro, which allows representing change proposals on the DSML design and discussing (and tracing back) possible solutions, comments and decisions arisen during the collaboration. Collaboro also incorporates a metric-based recommender system to help community members to define high-quality notations for the DSMLs. We also show how Collaboro can be used at the model-level to facilitate the collaborative specification of software models.

This paper introduces the architecture and the features of the HCM-L Modeler, a modeling tool supporting the Human Cognitive Modeling Language HCM-L and a comprehensive reasoning approach for Human Cognitive Models based on Answer Set Programming. The HCM-L tool has been developed using the ADOxx® meta modeling platform and following the principles of the Open Modeling Initiative: to provide open models that are formulated in an arbitrary, domain specific modeling language, which however is grounded in a common ontological framework, and therefore easily to translate in another language depending of the given purpose.

Domain specific modeling languages are of increasing importance for the development of software and other systems. Meta tools are needed to support rapid development of domain-specific solutions. Using the Eclipse Graphical Modeling Framework (GMF), modeling languages are defined by providing a meta model using the MOF/EMF approach. Up to now, GMF provides basic editing commands only. It does not support the definition of complex editing commands which would allow e.g. to insert a complex structure into a diagram in one step. As practical tool support for the design and generation of visual editors with complex editing operations based on graph transformation, an extended version of GMF has been developed and is presented in this paper.