Formal Modeling Method Research Articles

Formal modeling and verification method for Simulink-MDL requirement model

Abstract As complex safety-critical system software becomes more powerful, so does the complexity of its design requirements. Modeling and analyzing design requirements at an early stage has become an integral part of the entire development process for complex safety-critical system software. Simulink is a system modeling and simulation tool used in aviation and other fields. Its model is stored in the form of MDL files. ART (Avionics Requirement Tools) is a requirement modeling and analysis verification tool for the aviation field. It uses VRM (Variable Relation Model) as the theoretical model and can accept VRM and its extended subsets as input models and verify them in the tool. The work of this paper is oriented to the typical software requirements in the field of avionics systems and proposes a formal modeling and verification method for Simulink-MDL models. First, the composition form and structure of the MDL model are analyzed in the article. The functions and semantics of various elements in the model are given. Then a formal modeling method of the MDL model is given. Finally, a simplified version of the flight guidance control system is used for modeling and verification to demonstrate the usability and effectiveness of this method.

A verified low-level implementation and visualization of the adaptive exterior light and speed control system

In this article, we present an approach to the ABZ 2020 case study that differs from those usually presented at ABZ: Rather than using a (correct-by-construction) approach following a formal method, we use C for a low-level implementation instead. We strictly adhere to test-driven development for validation, and only afterwards apply model checking using CBMC for verification. While the approach has several benefits compared to the more rigorous approaches, it also provides less mathematical clarity and overall less thorough verification. In consequence, our realization of the ABZ case study serves as a baseline reference for comparison, allowing to assess the benefit provided by the various formal modeling languages, methods and tools.

Justice for war crimes in Ukraine: In search of an optimal model

The article is devoted to the investigation of the problems of finding and applying the optimal mechanism for bringing to international criminal responsibility persons guilty of committing war crimes on the territory of Ukraine. During the research a set of methods of scientific knowledge was used. Among them: dialectical and formal logic, analysis, abstraction, historical, comparative, system-structural and modeling methods. The investigated problem is considered through Ukraine's obligation to ensure compliance with the right to a fair trial for persons accused of committing war crimes. The paper provides current statistics on the number of war crimes committed on the territory of Ukraine in 2022 and, furthermore, provides their classification in accordance with the provisions of the Statute of the International Criminal Court. The known historical models of international criminal justice are highlighted, their general features and differences are given. The shortcomings of the model of judicial procedure for war crimes chosen by the Government of Ukraine are highlighted. As a result, the author's model of international criminal justice is proposed in accordance with the specifics of the situation in Ukraine.

A survey on the model-centered approaches to conceptual modeling of IoT systems

Internet of Things (IoT) is a system of connected objects, entities, devices, and components which share and transfer data over a network. Many papers are published on the topic of conceptual models in the IoT context, but it is difficult to assess the current status of the conceptual modeling approaches and methods for IoT systems. This paper presents an overview of the state of the art as well as discusses fundamental concepts, challenges and current research gaps with potential future agenda for conceptual modeling of IoT. Search facilities in the selected online repositories were used to identify the most relevant papers. The primary results were scanned and papers were selected according to the inclusion/exclusion criteria. Selected papers were assessed to extract data for the defined attributes. This paper confirms that there is a large body of research related to modeling of IoT systems. However, the results show that there is a lack of commonly agreed approaches and supporting formal methods for conceptual modeling of IoT systems. On the other hand, recent studies that apply model-based or model-driven development principles that use ontology or metamodel based approaches are promising due to systematic use of models as the primary means of a development process enabling for the dissemination of the methods further to the emerging fields such as smart cities, factories, transportation, hospitals, healthcare, hospitality and tourism, etc.

Modeling and analytics of multi-factor disease evolutionary process by fusing petri nets and machine learning methods

Recent years, informatization methods have been gradually applied to medical treatment, in which machine learning and evolutionary computation play an important role. However, the effective methods for the study of multi-factor disease evolutionary process are still largely open. There are some issues in the field of disease analysis, such as the lack of visual multi-factor disease evolution model and effective analysis methods. For a universal method of data analysis and medical diagnosis, the machine learning algorithms should be combined with the formal modeling methods to fully realize the complementary advantages, make model has the advantages of visualization and efficient data analysis. This work proposes a novel research idea for the modeling analysis of current multi-factor diseases and reveal its feasibility, so as to explore potential pharmaceutical targets and enable doctors and patients to better understand the evolution process of multi-factor diseases. It is worth mentioning that, in order to verify the feasibility of the proposed idea, we applied it to the analysis of the role of monoamine hormones in depression. The model incorporates the machine learning algorithms, and it finally outputs the pathogenic probability under different hormone levels, reflecting the importance of different factors on depression. The application case proved that we provide a clear process model and a novel research method for multi-factor disease evolutionary process analysis.

Error-Type—A Novel Set of Software Metrics for Software Fault Prediction

In software development, identifying software faults is an important task. The presence of faults not only reduces the quality of the software, but also increases the cost of development life cycle. Fault identification can be performed by analysing the characteristics of the buggy source codes from the past and predict the present ones based on the same characteristics using statistical or machine learning models. Many studies have been conducted to predict the fault proneness of software systems. However, most of them provide either inadequate or insufficient information and thus make the fault prediction task difficult. In this paper, we present a novel set of software metrics called Error-type software metrics, which provides prediction models with information about patterns of different types of Java runtime error. Particular, in this study, the ESM values consist of information of three common Java runtime errors which are Index Out Of Bounds Exception, Null Pointer Exception, and Class Cast Exception. Also, we proposed a methodology for modelling, extracting, and evaluating error patterns from software modules using Stream X-Machine (a formal modelling method) and machine learning techniques. The experimental results showed that the proposed Error-type software metrics could significantly improve the performances of machine learning models in fault-proneness prediction.

Keep All Objectives Satisfied (KAOS) to Event-B Models Transformation

Requirements engineering is an important aspect of the software development methodology because it is the first phase in every software development. The usefulness of formal language in requirements is well-established to ensure consistency. However, the conversion from informal requirements to the formal specification phase is still challenging because it requires advanced skills and much practice. Due to this challenge, we improve the conversion and relationship of these two phases by capturing requirements using KAOS approach and writing the formal specification using Event-B language. KAOS approach allows modeling the requirements through goal hierarchies, whereas Event-B is a formal system-level modeling and analysis method. This work proposes model transformation rules from KAOS model to Event-B model, along with implementing the rules, and evaluates the proposed rules using Mine Pump Controller case study. We used a model-driven approach, specifically model-to-model transformation, to transform KAOS model to Event-B model. We modeled the case study into the KAOS model to obtain the source model for our model transformation and extend the existing KAOS meta-model by adding four new meta-classes to ensure the KAOS model can accommodate all Event-B components. Our proposed rules manage to generate an abstract Event-B model, and a set of proof obligations have been used to verify the correctness of the model. However, the designers must manually perform the transition between the generated outputs to the Event-B platform.

Modelling and Analysis of Adaptive Cruise Control System Based on Synchronization Theory of Petri Nets

The ACC (adaptive cruise control) system has developed rapidly in recent years, and its reliability and safety have also attracted a lot of attention. The ACC system can realize automatic driving following the vehicle in the longitudinal range, and its reliability is closely related to the synchronization between two vehicles. Combined with formal modelling methods, this paper analyzes and detects the logical flaw that is poor synchronization in the following process of the ACC system from the perspective of synchronization. Aiming at avoiding this kind of logical flaw, this paper presents a novel optimized modelling solution based on the synchronization theory of Petri nets and further improves the calculation method of the synchronic distance. The simulation results reduce the token accumulation by an average of 91.357%, which demonstrates that the improved model can effectively improve reliability and reduce the risk of rear-end collision.

Innovation and Reform of Ideological and Political Course Mode in Colleges and Universities Based on Big Data Network Platform.

With the continuous development of the computer field, the Internet has become the main way of education in today's era. The development of computer technology and big data has brought innovation and opportunities to the teaching mode of ideological and political courses in colleges and universities. Due to the dynamic change of big data, there are many difficulties in the establishment of ideological and political course models in colleges and universities. This paper studies the innovation of ideological and political course modes in colleges and universities on the network platform under the background of big data. This paper mainly compares the traditional teaching mode and explores the formal modeling method of network platform education. The discrete dynamic modeling technology of the complex system is used to model the formal process of online education. Then, it carries out nonlinear prediction modeling for the operation efficiency and traffic change of the network platform under the big data environment and uses dynamic modeling to predict the learning effect of college students' ideological and political course mode. The results show that the formal method of education under dynamic modeling can improve the defects of traditional teaching and give full play to the advantages of network platform teaching. Improving the teaching mode of network platform can improve students' learning efficiency. Finally, in the dynamic model prediction, the problem of big data affecting the model results is improved, and the accuracy of the prediction model is improved.

Decoding the Role of Epigenetics in Breast Cancer Using Formal Modeling and Machine-Learning Methods

Breast carcinogenesis is known to be instigated by genetic and epigenetic modifications impacting multiple cellular signaling cascades, thus making its prevention and treatments a challenging endeavor. However, epigenetic modification, particularly DNA methylation-mediated silencing of key TSGs, is a hallmark of cancer progression. One such tumor suppressor gene (TSG) RUNX3 (Runt-related transcription factor 3) has been a new insight in breast cancer known to be suppressed due to local promoter hypermethylation mediated by DNA methyltransferase 1 (DNMT1). However, the precise mechanism of epigenetic-influenced silencing of the RUNX3 signaling resulting in cancer invasion and metastasis remains inadequately characterized. In this study, a biological regulatory network (BRN) has been designed to model the dynamics of the DNMT1–RUNX3 network augmented by other regulators such as p21, c-myc, and p53. For this purpose, the René Thomas qualitative modeling was applied to compute the unknown parameters and the subsequent trajectories signified important behaviors of the DNMT1–RUNX3 network (i.e., recovery cycle, homeostasis, and bifurcation state). As a result, the biological system was observed to invade cancer metastasis due to persistent activation of oncogene c-myc accompanied by consistent downregulation of TSG RUNX3. Conversely, homeostasis was achieved in the absence of c-myc and activated TSG RUNX3. Furthermore, DNMT1 was endorsed as a potential epigenetic drug target to be subjected to the implementation of machine-learning techniques for the classification of the active and inactive DNMT1 modulators. The best-performing ML model successfully classified the active and least-active DNMT1 inhibitors exhibiting 97% classification accuracy. Collectively, this study reveals the underlined epigenetic events responsible for RUNX3-implicated breast cancer metastasis along with the classification of DNMT1 modulators that can potentially drive the perception of epigenetic-based tumor therapy.

Effectiveness standards for investigation of corruption crimes: Theory and practice

The article deals with development of a doctrinal system of effectiveness standards for the investigation of corruption crimes. The study used a number of philosophical, general scientific and specific methods of gaining scientific knowledge, including: dialectical method, hermeneutic method, method of systemic and structural analysis, methods of analysis and synthesis, functional method, formal legal method and modeling method. It is proposed to define the investigation effectiveness as the feature of pre-trial investigation, which is characterized by the ability to achieve the tasks envisioned in Art. 2 of the CPC of Ukraine (Law No. 4651-VI, 2012) and can be assessed by checking the number of objectively necessary procedural actions and the effectiveness of making intermediate and final procedural decisions. It is emphasized that the general standards of investigation effectiveness, formulated by the case law of the ECHR, are partially taken into account in Art. 2 of the CPC of Ukraine (Law No. 4651-VI, 2012) through stating the need of investigation being efficient, complete and impartial. The authors formulate scientific approaches to determining the main criteria for the effectiveness of pre-trial investigation of corruption crimes.

Modeling of multilevel control system based on Event-B

Aiming at the problems existing in the traditional development method of multilevel control system, this paper proposes a formal modeling solution based on Event-B from the perspective of practical application. Based on the analysis of four synchronization modes and the principle of multilevel control system, a formal method is introduced. On this basis, by formulating the refined strategy of the multilevel control system model, the iUML-B model meeting the security requirements is established step by step. Through the automatic transformation function of the Rodin, the iUML-B model of multilevel control system is automatically transformed into Event-B mode. In order to ensure the safety of the system, this paper uses the ProB to simulate and record the event trajectory. The results show that the formal modeling method based on Event-B greatly improves the security and development efficiency of industrial control.

Hierarchical structure of a green supply chain

Since the past decades, environmental challenges have been increasing due to pollution and production costs. For sustainable development, a green supply chain integrates the sustainable environmental process into the traditional supply chain, reducing the cost of production, spur economic growth, and solving ecological issues. Thus, exploring the feasible design of green supply chain systems becomes an essential requirement for industry and commercial organisations. However, the green supply chain system usually integrates various systems currently used by the participants of supply chains. The design of such a large-scale system is quite costly through the conventional discrete event simulation-based approaches. Moreover, formal modelling method (e.g. Petri nets), as an alternative approach, provides formal and efficient support to model creation and analysis. However, the Petri nets cannot achieve compositional modelling, particularly for large-scale and complex systems, e.g., the green supply chain system. For improved compositionality, this paper proposes a hybrid modelling technique to integrate the compositional feature into Petri nets by combining with process algebra due to its superior capability in compositional modelling. The hybrid technique supports the modelling with Petri nets at first. It sorts the incidence matrix of Petri nets’ models to retrieves the mapping relation between Petri nets and performance evaluation process algebra (i.e. PEPA, a formal modelling method based on process algebra), which represents the compositional structure of Petri-net models. Hence, a compositional-structure constructing algorithm is designed to obtain all qualified PEPA hierarchical sub-models based on Petri net models, which combines Petri nets’ usability and the compositionality of PEPA for creating a novel and enhanced formal modelling technique that is particularly suitable for systems such as green supply chain systems.

Open Information Architecture for Seamless Integration of Renewable Energy Sources

Electric power systems are currently confronted with a fundamental paradigm change related to its planning and operation, mainly caused by the massive integration of renewables. To allow higher penetration of them within existing grid infrastructures, the “smart grid” makes more efficient use of existing resources by integrating appropriate information technologies. Utilising the benefits of such smart grids, it is necessary to develop new automation architectures and control strategies, as well as corresponding information and communication solutions. This makes it possible to effectively use and manage a large amount of dispersed generators and to utilise their “smart” capabilities. The scalability and openness of automation systems currently used by energy utilities have to be improved significantly for handling a high amount of distributed generators. This will be needed to meet the challenges of missing common and open interfaces, as well as the large number of different protocols. In the work at hand, these shortcomings have been tackled by a conceptual solution for open and interoperable information exchange and engineering of automation applications. The approach is characterised by remote controllable services, a generic communication concept, and a formal application modelling method for distributed energy resource components. Additionally, the specification of an access management scheme for distributed energy resources, taking into account different user roles in the smart grid, allowed for a fine-grained distinction of access rights for use cases and actors. As a concrete result of this work, a generic and open communication underlay for smart grid components was developed, providing a flexible and adaptable infrastructure and supporting future smart grid requirements and roll-out. A proof-of-concept validation of the remote controllable service concept based on this infrastructure has been conducted in appropriate laboratory environments to confirm the main benefits of this approach.

Tool-based automatic generation of digital assembly instructions

Formal modelling methods can be applied to tackle the complexity of production processes and varying product portfolios particularly affecting SMEs. As part of the project SynDiQuAss a software tool has been developed to automatically generate assembly instructions from a formal process model. Based on a template for a whole product family, the assembly process is decomposed into elementary tasks. In the second step available information such as CAD diagrams, required tools and parts is linked to provide cognitive assistance. The tool-based generation of assembly instructions can thus help increase both productivity and product quality for small lot sizes in manual assembly.

Conceptual State Analysis

Conceptual State Analysis (CSA) is the process of defining, exploring, and reasoning about state attributes and state spaces in complex system architectures. Model-Based State Analysis enhances CSA with formal modeling and analysis methods. We propose a process for generating the state vector of a given system architecture, based on a graph representation of the architecture’s model in Object-Process Methodology. A robust graph data structure that represents the model is queried to produce the architecture’s state space. The process facilitates analysis, reasoning, and model revision based on improved understanding of state vectors and state spaces. State attribute refinements within the model allow for model validity, viability, and reusability as the architecture evolves, with multiple agents, attributes, and attribute state values. The CSA approach advocates and facilitates careful, dynamic, and interactive state space exploration in lieu of exhaustive upfront enumeration of state space permutations. The results can be fed into other analysis, simulation, or visualization tools. We demonstrate CSA on driver assistance technology.

An Integrated Safety and Formal Analysis for Aircraft Landing System Based on SysML

The integration and interaction of multiple factors in large-scale system such as aircraft is the main reason of safety problem. For example, the aircraft can be affected by a variety of interactive factors due to changes in pilot conditions, avionics equipment and environmental state during flight. Aiming at the process of carrier aircraft landing, this paper proposes a formal modeling method based on System Modeling Language (SysML) to describe and analyze the safety of system. Firstly, the method based on SysML is detailed to model the structural and behavioural aspects, relying on the analysis of mission and/or behavior process. Then, the integrated method of SysML and Simulink, using the TGG method, is adopted to facilitate the analysis of the behavior processes. Finally, the attitude control during the aircraft landing process is taken as an example to assess the deviation and the dangerous time variation of the system in different disturbance degrees, which will help to make a better safety strategy.

Formal modelling of a sheet metal smart manufacturing system by using Petri nets and first-order predicate logic

This study introduces a developed method to a smart computer-aided design/manufacturing (CAD/CAM) system, where layout design, process planning, and comprehensive computerized numerical control (CNC) code generation can be implemented to satisfy laser cutting holes, tapping, irregular and complicated profile processing, engraving, and burr back-scraping. The smart CAD/CAM(SCAM) system is developed as a commercial software product or application and firstly applied to flexible sheet metal machining center (BGL 130R). In this study, a formal modeling method involving Petri nets and first-order predicate logic is proposed to develop the smart manufacturing system. High-level Petri nets are employed to achieve the formal application architecture design of data flow for various functions, and the first-order logic used to represent the process plan is defined and deduced according to the machining methods. The developed system possesses the following characteristics: (1) a sound and complete deductive system to implement various types of trajectory planning, automatic generation, and validation of the CNC code; (2) a convenient design input environment and readiness for re-design and modification by adding specific design functions and using standard design procedures on a widely used CAD/CAM package; (3) helpful for designers in sheet metal layout designing, layout interference detection, process planning validation, preprocess manufacturing operation of CNC code generation, and autodefinition of storable file names; and (4) formal and simple in human–computer interaction, automatic and intelligent in process operations, and satisfactory in terms of the requirements of the flexible sheet metal machining center (BGL 130R).

Formal development of an operation monitoring and control system for nuclear reactors using Event‐B method

Nuclear power plants are complex systems with many regulations, requirements, procedures, and operational constraints. The future autonomous safety monitoring and control system of nuclear plants require a constructive method in integrating and aggregating the accumulated knowledge database normally written in human language. For safety critical systems, formal methods such as model checking and theorem proving are used for verifying its conformance of safety requirements. However, formal specifications and implemented application codes are virtually unreadable for domain experts. To enhance this communication bottleneck and to boost productivity, we use semantic web technology to relate formal specifications with ontologies that are human-readable and have formal semantics. We introduce a nuclear reactor ontology of controlled vocabulary to link elements in a physical system and its Event-B model (a formal method for system-level modeling and analysis). Controlled vocabulary provides several benefits. It is still construction of a spoken language and thus, human readable and transparent. Their formal semantics make it easy to integrate them to the counterparts in their specification. We can generate system logs those are both human and machine friendly. Practitioners can write ad hoc query using SPARQL Protocol and RDF Query Language (SPARQL). As a proof of concept of our methodology, we build a system for safety monitoring and control of a nuclear reactor. We prototype our monitoring system in Event-B model and verify that it satisfies safety requirements and constraints. Then we build an OWL 2 ontology for the semantic web from the Event-B model annotating all metrics and events of the system monitors.

Model Transformation as Conservative Theory-Transformation.

Model transformations play a central role in model-driven software development. Hence, logical unsafe model transformation can result in erroneous systems. Still, most model transformations are written in languages that do not provide built-in safeness guarantees.We present a new technique to construct tool support for domain-specific languages (DSLs) inside the interactive theorem prover environment Isabelle. Our approach is based on modeling the DSL formally in higher-order logic (HOL), modeling the API of Isabelle inside it, and defining the transformation between these two. Reflection via the powerful code generators yields code that can be integrated as extension into Isabelle and its user interface. Moreover, we use code generation to produce tactic code which is bound to appropriate command-level syntax.Our approach ensures the logical safeness (conservativity) of the theorem prover extension and, thus, provides a certified tool for the DSL in all aspects: the deductive capacities of theorem prover, code generation, and IDE support. We demonstrate our approach by extending Isabelle/HOL with support for UML/OCL and, more generally, providing support for a formal object-oriented modeling method.