A DEVS-based pivotal modeling formalism and its verification and validation framework

Currently, software systems are operated in a dynamic and uncertain environment, making it difficult to predict the operating environment. Particularly, the Internet of Things (IoT) interconnects several entities, users, and information resources with services. Therefore, IoT systems can dynamically create various environments at runtime. Consequently, to support the dynamic IoT environment, an efficient verification method is required for IoT systems. Model checking is one of the formal methods for verification of concurrent systems, which is applied in several software fields. However, model checking has a chronic problem (i.e., state explosion) that obstructs the verification at runtime. To overcome this limitation, one possible approach is to abstract the system design as expression forms and then perform verification by solving the expressions. To apply this approach, the abstraction and verification processes need to be performed at a reasonable time. In this article, we focused on developing an efficient model checking method during the IoT system runtime verification. A cache mechanism is proposed that reduces the computational time for abstraction and verification, which was validated through experiments. Additionally, the comparison of other model checking tools (such as RINGA, CadenceSMV, NuSMV, and nuXmv) reveals that the proposed approach is more efficient at runtime.

Model Checking represents a mathematical method of formal verification which can prove that model satisfies its specified requirements. This article describes an approach that utilizes Function Block Diagram (FBD) models. The key benefit of this approach is the automatic transformation of the original model into a formal model which can be checked by Model Checking. In this way Model Checking can be easier integrated in the standard development process. The presented approach was developed together with the new verification process. This process can be used for the verification of safety-critical systems.

Verification for interaction protocol of Web services is crucial to both implementation and composition of Web services. The verification process can prove important and desirable properties of the control flow and data flow of Web services. Model checking is a promising technique for verification and validation of software systems. In this paper, we present a model checking framework to specifying and verifying Web service flow based on annotated OWL-S. By using annotation layers, an OWL-S process model can be extended with constraints (like time properties) information. An underlying OWL-S model and one or more constraint annotation layers compose a complete specification of a Web process imposed specific constraints. By transforming the annotated OWL-S model to a TCPN (time constraints Petri net) model, Web service flow can be analyzed and verified. The method allows us to add conveniently constraints information to a Web process model, and state whether a process satisfies given properties without actual execution based on its specification.

The multi-domain model established based on Modelica can effectively describe the dynamics and randomicity of failure behavior in complex systems. Firstly, the characteristics of multi-domain model are described, and the modeling methodology of failure behavior in complex systems based on multi-domain language is introduced; then the multi-domain model of actuator is established based on the components behavioral model library; finally, the actuator system is simulated and results are analyzed. The results show that not only the dynamic failure behaviors of complex systems, transfer process of different behaviors and performance fluctuations caused by failure behavior, but also the stochastic time when fault happens and uncertainty of parameters can be described by the proposed modeling methodology. It is validated that the methodology is useful for engineering application.

Unified Modeling Language is being used for modeling of business processes, real-time systems, embedded systems and hybrid systems. In software engineering, there are different techniques for verification of such systems. Model checking is one of the techniques for the automatic verification of software models. Earlier, these model were verified by sequential model checking tools. For very large complex systems, parallel verification can save verification time. DiVinE is a model checking tool for both CPUs and GPUs clusters to perform parallel linear time logic (LTL) verification of systems. In this paper, we propose a parallel verification methodology for UML models using DiVinE tool. We explain this methodology by the case study example of fuel filling machine.

Model checking of systems with many identical timed processes

Forecasting a system's behavior is an essential task encountering the complex systems theory. Machine learning offers supervised algorithms, e.g., recurrent neural networks and reservoir computers that predict the behavior of model systems whose states consist of multidimensional time series. In real life, we often have limited information about the behavior of complex systems. The brightest example is the brain neural network described by the electroencephalogram. Forecasting the behavior of these systems is a more challenging task but provides a potential for real-life application. Here, we trained reservoir computer to predict the macroscopic signal produced by the network of phase oscillators. The Lyapunov analysis revealed the chaotic nature of the signal and reservoir computer failed to forecast it. Augmenting the feature space using Takkens' theorem improved the quality of forecasting. RC achieved the best prediction score when the number of signals coincided with the embedding dimension estimated via the nearest false neighbors method. We found that short-time prediction required a large number of features, while long-time prediction utilizes a limited number of features. These results refer to the bias-variance trade-off, an important concept in machine learning.

Sustaining and optimising complex systems are often challenging problems as such systems contain numerous variables that are interacting with each other in a nonlinear manner. Application of integrated sustainability principles in a complex system (e.g., the Earth’s global climate, social organisations, Boeing’s supply chain, automotive products and plants’ operations, etc.) is also a challenging process. This is due to the interactions between numerous parameters such as economic, ecological, technological, environmental and social factors being required for the life assessment of such a system. Functionality and flexibility assessment of a complex system is a major factor for anticipating the systems’ responses to changes and interruptions. This study outlines generic mathematical and computational approaches to solving the nonlinear dynamical behaviour of complex systems. The goal is to explain the modelling and simulation of system’s responses experiencing interaction change or interruption (i.e., interactive disruption). Having this knowledge will allow the optimisation of systems’ efficiency and would ultimately reduce the system’s total costs. Although, many research works have studied integrated sustainability behaviour of complex systems, this study presents a generic mathematical and computational framework to explain the behaviour of the system following interactive changes and interruptions. Moreover, a dynamic adaptive response of the global system over time should be taken into account. This dynamic behaviour can capture the interactive behaviour of components and sub-systems within a complex global system. Such assessment would benefit many systems including information systems. Due to emergence and expansion of big data analytics and cloud computing systems, such life-cycle assessments can be considered as a strategic planning framework before implementation of such information systems.

Reactive systems are becoming extremely complex with the huge increase in high technologies. Despite technical improvements, the increasing size of the systems makes the introduction of a wide range of potential errors easier. Among reactive systems, the asynchronous systems communicating by exchanging messages via buffer queues are often characterized by a vast number of possible behaviors. To cope with this difficulty, manufacturers of industrial systems make significant efforts in testing and simulation to successfully pass the certification process. Nevertheless revealing errors and bugs in this huge number of behaviors remains a very difficult activity. An alternative method is to adopt formal methods, and to use exhaustive and automatic verification tools such as model-checkers. Model-checking algorithms can be used to verify requirements of a model formally and automatically. Several model checkers as (Berthomieu et al., 2004; Holzmann, 1997; Larsen et al., 1997), have been developed to help the verification of concurrent asynchronous systems. It is well known that an important issue that limits the application of model checking techniques in industrial software projects is the combinatorial explosion problem (Clarke et al., 1986; Holzmann & Peled, 1994; Park & Kwon, 2006). Because of the internal complexity of developed software, model checking of requirements over the system behavioral models could lead to an unmanageable state space. The approach described in this chapter presents an exploratory work to provide solutions to the problems mentioned above. It is based on two joint ideas: first, to reduce behaviors system to be validated during model-checking and secondly, help the user to specify the formal properties to check. For this, we propose to specify the behavior of the entities that compose the system environment. These entities interact with the system. Their behaviors are described by use cases (scenarios) called here contexts. They describe how the environment interacts with the system. Each context corresponds to an operational phase identified as system initialization, reconfiguration, graceful degradation, etc.. In addition, each context is associated with a set of properties to check. The aim is to guide the model-checker to focus on a restriction of the system behavior for verification of specific properties instead on exploring the global system automaton.

With the development of the nuclear technology, the instrumentation and control (I&C) systems have evolved from the analog systems to the current state-of-the-art digital systems. It has been reported that China has recently developed the digital systems based on Field Programmable Gate Array (FPGA) in CAP1400 nuclear power plant. And the lack of methods in the verification and validation work of the FPGA systems has become an important issue. This thesis describes the basic principles of FPGA, and the development process of FPGA. And then, the thesis proposes an effective improved method—formal verification, describing three methods of formal verification in detail, namely theorem proof, model checking, and equivalence proof. Describing the FPGA verification methodology and pointing out the shortcomings of traditional simulation, comparing the formal verification and traditional simulation verification in terms of complexity, timing, and applications. We also discussed the importance of formal verification method in FPGA. We selected the temperature and power control chip based on FPGA as an example, using System Verilog Assertions (SVA) method of model checking, and verifying the SRAM controller module and the internal calculation module. Through the analysis of the results, this paper proved the feasibility of formal verification methods in the instrumentation and control system of nuclear power plants, and provided some references of verification work for other system chips in instrumentation and control of nuclear power plant in the future work. The thesis showed that verification engineers can use the formal verification method based on SVA to verify the robustness of the system quickly and accurately. This method improves the controllability and observability which are the main drawbacks of the traditional simulation verification. It also avoids several issues in the debug process of traditional simulation verification, improving the accuracy and completeness of the chip verification.

Real-time system verification must deal with a special notion of ‘fairness’, i.e., clocks must always be able to progress. A system run which prevents clocks from progressing unboundedly is known as Zeno. Zeno runs are infeasible in reality and thus must be pruned during system verification. Though zone abstraction is an effective technique for model checking real-time systems, it is known that zone graphs (e.g., those generated from Timed Automata models) are too abstract to directly infer time progress and hence non-Zenoness. As a result, model checking with non-Zenoness (i.e., existence of a non-Zeno counterexample) based on zone graphs only is infeasible. In our previous work [23], we show that model checking Stateful Timed CSP with non-Zenoness based on zone graphs only is feasible, due to the difference between Stateful Timed CSP and Timed Automata. Nonetheless, the algorithm proposed in [23] requires to associate each time process construct with a unique clock, which could enlarge the state space (compared to model checking without non-Zenoness) significantly. In this paper, we improve our previous work by combining the checking algorithm with a clock-symmetry reduction method. The proposed algorithm has been realized in the PAT model checker for model checking LTL properties with non-Zenoness. The experimental results show that the improved algorithm significantly outperforms the previous work.KeywordsModel CheckLabel Transition SystemSymmetry ReductionStrongly Connected ComponentTime AutomatonThese 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.

Non-Commutativity, Incompatibility, Emergent Behavior and Decision Support Systems

Increasingly, management scientists have paid attention to developments in other sciences, which could be of interest for improved understanding of the complex behavior of systems in a managerial context. The sciences which are working with non-linear and dynamic systems are multiple and therefore we want to limit this overview. Those sciences which we have a look into are: physics, neurobiology, cognitive psychology and computer sciences. For a better understanding of systems behavior (e.g. market behavior) we need to attack some theoretical concepts. We will limit them as much as possible. For each concept a brief theoretical introduction is given but we also try to make it more accessible for the manager via examples. Each of the concepts refers to a limited bibliography in itself. Some reference works will be given which allows the interested reader to go a little further, without becoming too involved in the details. The suggested books, in turn, all have an extended bibliography for the very interested or very advanced reader.

Nowadays the short messaging service (SMS) has been used in direct sales and network marketing which is a part of e-business. Many systems integrate information system using mobile phone as a medium of communication in ensuring business processes become more effective and conducive. The intention of the system is to enhance the connection and networking in management system for direct sales activities. However, as the SMS services have been used extensively by the mobile users, there are several exceptional issues occurred during the runtime of each state of the e-business processes. Consequently, the correctness and secureness of the system performance have not been confidently trusted. Therefore, in this paper we propose a design of model checking agent for SMS management system to address the issue. Agents become a platform for model checking in handling the verification and validation processes in SMS management system. We have developed a model checking agent as a reliable tool for evaluating the failure of protocols in SMS management system. We have also analyzed the propose model which has contributed to the quality of SMS messages and increase the failure detection in ebusiness process.

Model checking as an approach to the automatic verification of finite state systems has focussed predominantly on system specifications expressed in temporal logic. In the distributed systems community, logics of knowledge (epistemic logics) have been advocated for expressing desirable properties of protocols and systems. A range of logics combining temporal and epistemic components have been developed for this purpose. However, the model checking problem for temporal logics of knowledge has received (comparatively) little attention. In this paper, we address ourselves to this problem. Following a brief survey of the relevant issues and literature, we introduce a temporal logic of knowledge (Halpern and Vardi’s logic CKL n). We then develop an approach to CKL n model checking that combines ideas from the interpreted systems semantics for knowledge with the logic of local propositions developed by Engelhardt et al. With our approach, local propositions provide a means to reduce CKL n model checking to linear temporal logic model checking. After introducing and exploring the ideas underpinning our approach, we present a case study (the bit transmission problem) in which spin was used to establish temporal epistemic properties of a system implemented in PROMELA.