Comparative Analysis of Workbenches to Support DSMLs: Discussion with Non-Trivial Model-Driven Development Needs

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.

The use of domain-specific modeling languages (DSMLs) results in higher productivity during the development process. This is accomplished by raising the level of abstraction during design and focusing on domain concepts rather than low-level implementation details. Unlike other development paradigms, little work has been done in determining and measuring the claimed benefits of using DSMLs.In this paper, we propose a new approach to determine the effort involved in creating and using DSML models to develop applications and to manage the behavior of applications at runtime. The approach involves a classification of the effort involved, and definition of relevant metrics to measure the effort for each category. A case study is presented that shows how we applied the proposed metrics during the development and execution of an application using three different DSMLs.

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.

Building conceptual models for software design, in particular for high-tech applications such as smart home systems, is a complex task that significantly affects the efficiency of their development processes. One of the innovative methods of solving this problem is the use of domain-specific modeling languages (DSMLs), which can reduce the time and other project resources required to create such systems. The subject of research in this paper is approaches to the development of DSML for Smart Home systems as a separate class of Internet of Things systems. The purpose of this work is to propose an approach to the development of DSMLs based on a model of variability of the properties of such a system. The following tasks are being solved: analysis of some existing approaches to the creation of DSMLs; construction of a multifaceted classification of requirements for them, application of these requirements to the design of the syntax of a specific DSML-V for the creation of variable software in smart home systems; development of a technological scheme and quantitative metrics for experimental evaluation of the effectiveness of the proposed approach. The following methods are used: variability modeling based on the property model, formal notations for describing the syntax of the DSML-V language, and the use of the open CASE tool metaDepth. Results: a multifaceted classification of requirements for a broad class of DSML languages is built; the basic syntactic constructions of the DSML-V language are developed to support the properties of software variability of "Smart Home" systems; a formal description of such syntax in the Backus-Naur notation is given; a technological scheme for compiling DSML-V specifications into the syntax of the language of the open CASE tool metaDepth is created; the effectiveness of the proposed approach using quantitative metrics is experimentally investigated. Conclusions: the proposed method of developing a specialized problem-oriented language for smart home systems allows for multilevel modeling of the variability properties of its software components and provides an increase in the efficiency of programming such models by about 14% compared to existing approaches.

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.

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.

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.

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.

Domain specific languages have been used in modeling and simulation as tools for model description. In recent years, the efforts toward enabling simulation reproducibility have motivated the use of domain specific languages also as the means with which to express experiment specifications. In simulation areas ranging from computational biology to computer networks, the emerging trend is to treat the experimentation process as a first class object. Domain specific languages serve to specify individual sub-tasks in this process, such as configuration, observation, analysis, and evaluation of experimental results. Additionally, they can be used in a broader scope, for instance, to describe formally the experiment's goals. The research and development of domain specific languages for experiment specification explores all of these and additional possible applications. In this paper, we discuss various existing approaches for defining this type of domain specific languages and present a critical analysis of our findings.

Recently, there is a growing interest in Systems of Systems (SoS), their architecture, security and application domains. However, their specific characteristics such as the operational independence of SoS constituent systems (CS), the absence of central authority and their emergent behavior make the modeling of their structure, behavior and security a complex task. One of the current main security challenges in the context of SoS is the cascading attack problem. The challenge is to predict the concatenation/sequence of CS's vulnerabilities that could be triggered resulting in destructive cascading failures and take corrective actions to reduce the cost, development time and effect of later changes. In this paper, we propose a domain specific modeling language (DSML) to represent SoS security rchitecture. Having SoS security models will enable the discovery, analysis and resolution of cascading attacks, in the architecture phase, preventing development time and cost wastage. Following a Model Driven Engineering (MDE) approach, we generate a graphical editor for our DSML and use it to model a Smart Campus case study.

In order to assist domain experts, several tools exist for the definition of graphical or textual domain specific modeling languages (DSMLs). The resulting models are useful, but not sufficient, for an overall understanding of the system, especially when formal methods are being applied. Indeed, formal methods failures often result from misunderstandings of the requirements, even if the system is entirely proved. This is confirmed by several industrial experiments which showed that the poor readability of the formal notations is not convenient for communication with domain experts and hence the validation activity is often tedious, time consuming and complex. In order to circumvent this shortcoming, we propose to make domain specific models provable and also executable thanks to the animation of their expected behaviour directly in a dedicated DSML tool. Our approach starts from an intuitive description of the system’s operational semantics thanks to high-level Petri-nets which abstract away structural constraints and focus on safety-critical behaviours. Then we take benefit of the B method in order to refine and prove these operational semantics on the one hand, and to merge them with the static semantics of a given DSML, on the other hand. This work is applied to the design of ERTMS/ETCS 3 which is an emergent solution for railway system management.

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.

The ever increasing societal demand for the timely availability of newer and feature-rich but highly dependable network-centric applications imposes the need for these applications to be constructed by the composition, assembly and deployment of off-the-shelf infrastructure and domain-specific services building blocks. Service oriented architecture (SOA) is an emerging paradigm to build applications in this manner by defining a choreography of loosely coupled building blocks. However, current research in SOA does not yet address the per for mobility (i.e., performance and dependability) challenges of these modern applications. Our research is developing novel mechanisms to address these challenges. We initially focus on the composition and configuration of the infrastructure hosting the individual services. We illustrate the use of domain-specific modeling languages and model weavers to model infrastructure composition using middleware building blocks, and to enhance these models with the desired performability attributes. We also demonstrate the use of generative tools that synthesize metadata from these models for performability validation using analytical, simulation and empirical benchmarking tools.

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.

Frameworks support application development improving productivity and quality. However, due to the number of hot stops to configure them, reusing frameworks may be a complex task which can make developers misuse them and insert defects in the application code. In order to reduce the complexity of this task, we propose increase its abstraction level by using Domain-Specific Modeling Languages (DSML) based on framework features to model and to generate applications that reuse these frameworks. In our approach, framework features and their hot spots are identified from an analysis of its source code and documentation, and then a DSML and a set of templates are constructed. With this DSML, applications reusing the framework can be modeled and generated, protecting developers from framework complexity and decreasing the time spent on the implementation. We illustrate our approach using GRENJ framework as example.KeywordsFrameworkFeatureDomain-specific modeling languageTemplateCode generation