Software and Systems Modeling最新文献

Verifying safety requirements by model checking becomes increasingly important for safety-critical applications. For the validity of such proof in practice, the model needs to capture the actual behavior of the real system, which could be tested by containment checks of real observation traces. Basic equivalence checks, however, are not applicable if the system is only partially or imprecisely observable, if the model abstracts from explicit states with symbolic semantics, or if the checks are not expressible in the logics supported by a model checker. In this article, we solve the problem of observation containment checking in timed automata via reachability checking on tester systems. We introduce the logic SRL (sequence reachability logic) to express observations as sequences of delayed reachability properties. Through SBLL (introduced by Aceto et al.) as intermediate logic, we synthesize a set of matcher model templates for partial and imprecise observations and further extend these templates for the case of limited state accessibility in a model. For the obtained matching traces, we define the back-transformation into the original model domain and formally prove the correctness of the transformation. We implemented the observation matching approach, and apply it to a set of 7 demo and 3 case study models with different levels of observability. The results show that all positive and negative observations are correctly classified, and that the most advanced matcher model instance still offers average run times between 0.1 and 1 s in all but 3 scenarios.

The complexity of safety-critical systems is continuously increasing. To create safe systems despite the complexity, the system development requires a strong integration of system design and safety activities. A promising choice for integrating system design and safety activities are model-based approaches. They can help to handle complexity through abstraction, automation, and reuse and are applied to design, analyze, and assure systems. In practice, however, there is often a disconnect between the model-based design and safety activities. At the same time, there is often a delay until recent approaches are available in model-based frameworks. As a result, the advantages of the models are often not fully utilized. Therefore, this article proposes a framework that integrates recent approaches for system design (model-based systems engineering), safety analysis (system-theoretic process analysis), and safety assurance (goal structuring notation). The framework is implemented in the systems modeling language (SysML), and the focus is placed on the connection between the safety analysis and safety assurance activities. It is shown how the model-based integration enables tool assistance for the systematic creation, analysis, and maintenance of safety artifacts. The framework is demonstrated with the system design, safety analysis, and safety assurance of a collision avoidance system for aircraft. The model-based nature of the design and safety activities is utilized to support the systematic generation, analysis, and maintenance of safety artifacts.

Method engineering emerged in the 1990s as a discipline aiming to design, construct, and adapt methods, techniques, and tools for the development of information systems. By executing a method step by step, users can follow a well-defined process to achieve the intended results for which the method was created. To create methods in a more guided and systematic manner, a framework of methods can serve as a template. This allows individuals to leverage the expertise of method engineers who have consolidated their best practices within these frameworks. However, the creation and adoption of a method can be challenging in the absence of tools to support these activities. Additionally, method engineers may lack the programming skills required to implement such tools. In this context, we extend an approach inspired by the low-code paradigm for method engineering. By integrating construction rules for guidance (called here protocols), the goal of this approach is to assist method engineers in creating new methods or adapting existing frameworks. It automatically provides tool support, enabling method experts to effectively execute the method. This paper builds upon previous work and presents the approach through a proof-of-concept implementation, LOMET. We present a second version of LOMET, which has been refined based on feedback received during an empirical evaluation conducted through semi-structured interviews.

Language technologies are gaining momentum as textual information saturates social networks and media outlets, compounded by the growing role of fake news and disinformation. In this context, approaches to represent and analyse public speeches, news releases, social media posts and other types of discourses are becoming crucial. Although there is a large body of literature on text-based machine learning, it tends to focus on lexical and syntactical issues rather than semantic or pragmatic. Being useful, these advances cannot tackle the nuanced and highly context-dependent problems of discourse evaluation that society demands. In this paper, we present IAT/ML, a metamodel and modelling approach to represent and analyse discourses. IAT/ML focuses on semantic and pragmatic issues, thus tackling a little researched area in language technologies. It does so by combining three different modelling approaches: ontological, which focuses on what the discourse is about; argumentation, which deals with how the text justifies what it says; and agency, which provides insights into the speakers’ beliefs, desires and intentions. Together, these three modelling approaches make IAT/ML a comprehensive solution to represent and analyse complex discourses towards their understanding, evaluation and fact checking.

The paper proposes universal conceptual modeling, conceptual modeling that strives to be as general-purpose as possible and accessible to anyone, professionals and non-experts alike. The idea of universal conceptual modeling is meant to catalyze new thinking in conceptual modeling and be used to evaluate and develop conceptual modeling solutions, such as modeling languages, approaches for requirements elicitation, or modeling tools. These modeling solutions should be usable by as many people and design agents as possible and for as many purposes as possible, aspiring to the ideals of universal conceptual modeling. We propose foundations of universal conceptual modeling in the form of six principles: flexibility, accessibility, ubiquity, minimalism, primitivism, and modularity. We then demonstrate the utility of these principles to evaluate existing conceptual modeling languages and understand conceptual modeling practices. Finally, we propose future research opportunities meant to realize the ideals of universal conceptual modeling.

The integration of Large Language Models (LLMs) in software modeling tasks presents both opportunities and challenges. This Expert Voice addresses a significant gap in the evaluation of these models, advocating for the need for standardized benchmarking frameworks. Recognizing the potential variability in prompt strategies, LLM outputs, and solution space, we propose a conceptual framework to assess their quality in software model generation. This framework aims to pave the way for standardization of the benchmarking process, ensuring consistent and objective evaluation of LLMs in software modeling. Our conceptual framework is illustrated using UML class diagrams as a running example.

Understanding and interpreting vast amounts of information is pivotal in the contemporary data-rich age. Data visualization has emerged as a significant measure of comprehending these data. Similarly, an appropriate visualization can also enhance software modeling by providing straightforward and interactive representations. However, current data visualization methods predominantly require users to have data visualization-related expertise, which is usually challenging to obtain in reality. It is essential to bridge the gap between visualization requirements and visualization solutions for non-expert users, assisting them in automatically operationalizing their visualization requirements. This paper proposes a MUltilayer framework for analyzing and operationalizing visualization REQuirements that automatically derives appropriate visualization solutions based on users’ requirements. Specifically, we systematically investigate the connections among visualization requirements, visual variable characteristics, visual variable attributes, and visualization solutions, based on which we establish a conceptual framework that characterizes the relationships among different layers. Our proposal contributes to not only automatically operationalizing visualization requirements but also providing meaningful explanations for the derived visualization solutions. To promote our proposal and pragmatically benefit real users, we have developed and deployed a prototype tool based on the proposed framework, which is publicly available at https://reqdv.vmasks.fun. To evaluate our proposed framework, we conducted an initial controlled experiment with 44 participants to test the performance of the evolved mappings within our framework. Based on the expert’s feedback, we refined the mappings and incorporated a ranking system for visualization solutions tailored to specific requirements. To assess the current method, a subsequent experiment with another group of 44 participants and a focused case study involving two new participants were carried out. The results demonstrate that users perceive that the current method accelerates task completion, especially for complex tasks, by efficiently narrowing down options and prioritizing them. This approach is particularly advantageous for users with limited data visualization experience. Besides, the multilayer framework can be used to inspire the visualization of models in the software modeling community.

Business process modeling is essential for organizations to comprehend, analyze, and enhance their business operations. The business process model and notation (BPMN) is a standard widely adopted for illustrating business processes. However, it falls short when modeling roles, interactions, and responsibilities within complex modern processes that involve digital, human, and non-human entities, typically found in cyber-physical systems (CPS). In this paper, we introduce Role-based BPMN (RBPMN), a standard-compliant extension of BPMN 2.0 that distinctly depicts roles and their interactions within business processes. We underscore the value of RBPMN and a role-based context modeling approach through a modeling example in CPS that facilitates the representation of role-based variations in the process flow, namely a production process in a smart factory. Our findings suggest that RBPMN is a valuable BPMN extension that enhances the expressiveness, variability, and comprehensiveness of business process models, especially in complex and context-sensitive processes.

The formal verification of the properties of semi-formal models can make it easier to ensure their security and safety. However, this task is generally cumbersome for non-specialists in formal verification, particularly in an industrial context. This paper introduces an evaluation of four formal verification tools on an industrial case, called a Life Cycle Management System (LCMS). This LCMS makes it possible to deploy Product-Service Systems (PSSs) to customers using Systems-on-Chip (SoC). A PSS is a business model in which products and services are tightly connected and whose objective is to optimize the use of products, with a positive environmental impact. A SoC can embed hardware security; however, a LCMS must be secure from end to end, which requires a verification not only of the used protocol (in this case, a blockchain-based protocol), but also of the whole architecture. For that purpose, semi-formal UML models of a LCMS were first specified and designed with their associated properties, then improved in order to be formally verifiable. Despite being more complex, they remain capable of being processed by dedicated tools. In this paper, Verifpal and ProVerif, two formal cryptographic protocol verifiers, are used and evaluated for the cryptographic protocol and AnimUML (developed by one of the authors) and HugoRT, two verification tools for behavior and UML for the architectural model are evaluated. These tools are assessed and compared according to their coverage of properties and state spaces, limitations, and usability for non-specialists. Some limitations of the approach itself are also provided.

The domain of Enterprise Information Systems Engineering uses many different conceptual modelling languages and methods to specify the requirements of a system under development. The complexity of the systems under development may require addressing different perspectives with different models, such as the data and process perspectives. The modeller will thus have to choose the appropriate (set of) modelling languages according to their specific modelling goal. Given that the different aspects relate to a single system, ideally, the models that capture the different perspectives should be aligned and consistent to ensure their integration. Each candidate (set of) modelling languages comes with advantages and disadvantages. To make an informed choice in this matter, the modeller should select a number of criteria relevant to their problem domain and compare candidate modelling languages based on these criteria. A comprehensive evaluation framework for integrated modelling approaches, that considers more general aspects such as understandability, ease of use, model quality, etc. besides the ability to model the desired aspects, does not yet exist and is therefore the focus of this paper. In recent years, several combinations of modelling languages have been investigated. Amongst these combinations, data + process modelling has attracted a lot of interest, and, interestingly, evaluation frameworks for this combination have been proposed as well. Therefore, this paper will primarily focus on the integrated multi-modelling of data and processes, including the process-related viewpoints of users and authorisations. The contribution of this paper is two-fold: on a theoretical level, the paper provides an overview of existing evaluation frameworks in the literature, builds a more complete set of evaluation criteria and proposes a unified taxonomy for the classification of these evaluation criteria (TEC-MAP); on a practical level, the paper provides guidance and support to the modeller for selecting the appropriate evaluation criteria for their problem domain and presents three examples of the application of TEC-MAP.