Verification Of Cyber-physical Systems Research Articles

Unified Graphical Co-modelling, Analysis and Verification of Cyber-physical Systems by Combining AADL and Simulink/Stateflow

The design of safety-critical cyber-physical systems (CPSs) involve several dimensions, including physics, hardware rchitecture and software functionality. It is desirable to design CPSs by taking these issues into account uniformly and yet, few existing design workflows support this aim. For instance, AADL is an architecturecentric modelling formalism for CPSs, which focuses on modelling architecture and prototyping real-time hardware platforms, but it delegates physical and software behavioral models to so-called annexes. By contrast, Simulink/Stateflow (S/S) focuses on modelling interacting physical and software behaviors, but does not render the non-functional characteristics of their hardware platforms. To address this issue, in [1], we proposed the combination of AADL and S/S, called AADL S/S, to comodel CPSs and presented a method to uniformly analyse and verify them. AADL S/S provides a unified graphical co-modelling environment for CPS design and supports simulation through C code generation. Also, [1] presented a formal semantics of AADL S/S by translation to Hybrid Communicating Sequential Processes (HCSP), yielding a deductive verification framework of the combined models using Hybrid Hoare Logic (HHL). Additionally, [1] proved the correctness of the translation of AADL S/S to HCSP.

Any-Horizon Uniform Random Sampling and Enumeration of Constrained Scenarios for Simulation-Based Formal Verification

Model-based approaches to the verification of non-terminating Cyber-Physical Systems (CPSs) usually rely on numerical simulation of the System Under Verification (SUV) model under input scenarios of possibly varying duration, chosen among those satisfying given constraints. Such constraints typically stem from requirements (or assumptions) on the SUV inputs and its operational environment as well as from the enforcement of additional conditions aiming at, e.g., prioritising the (often extremely long) verification activity, by, e.g., focusing on scenarios explicitly exercising selected requirements, or avoiding vacuity in their satisfaction. In this setting, the possibility to efficiently sample at random (with a known distribution, e.g., uniformly) within, or to efficiently enumerate (possibly in a uniformly random order) scenarios among those satisfying the given constraints is a key enabler for the viability of the verification process, e.g., via simulation-based statistical model checking. Unfortunately, in case of non-trivial combinations of constraints, iterative approaches like Markovian random walks in the space of sequences of inputs in general fail in extracting scenarios according to a given distribution, and can be very inefficient to produce legal scenarios of interest. We show how, given a set of constraints on the input scenarios succinctly defined by finite memory monitors, a data structure (scenario generator) can be synthesised, from which any-horizon scenarios satisfying the input constraints can be efficiently extracted by (possibly uniform) random sampling or (randomised) enumeration. Our approach enables seamless support to virtually all simulation-based approaches to CPS verification, ranging from simple random testing to statistical model checking and formal (i.e., exhaustive) verification.

Unified graphical co-modeling, analysis and verification of cyber-physical systems by combining AADL and Simulink/Stateflow

The efficient design of safety-critical cyber-physical systems (CPS) requires the co-modeling and -verification of its physics, architecture and functionalities. Existing co-modeling formalisms do not account for these three design aspects into account uniformly. AADL is a precise formalism for modeling architecture and prototyping real-time hardware platforms, but it delegates co-modeling physical and software behaviors to so-called annexes. By contrast, Simulink/Stateflow (S/S) is strong for modeling interacting physical and software behaviors, but weak for modeling architecture and hardware platforms. To address this issue, this paper considers the combination of AADL and S/S to co-model CPSs and presents a method to uniformly analyze and verify this combination. AADL⊕S/S provides a unified graphical co-modeling environment for CPS design and supports simulation through C code generation. We present a formal semantics of AADL⊕S/S by translating it to Hybrid Communicating Sequential Processes (HCSP), which yields a deductive verification framework for AADL⊕S/S models based on Hybrid Hoare Logic (HHL). We also prove the correctness of the translation of AADL⊕S/S to HCSP. The effectiveness of our approach is illustrated by the realistically-scaled case study of an automatic cruise control system.

PDF: Path-Oriented, Derivative-Free Approach for Safety Falsification of Nonlinear and Nondeterministic CPS

Cyber-physical systems (CPSs) integrate discrete computations with continuous physical processes and can be highly nonlinear and nondeterministic. Unlike the verification of CPS, which is difficult to handle, the falsification of CPS fulfills certain requirements from testing by seeking witness behavior of these systems and is easier to conduct. However, existing falsification techniques may fail to support the general complex CPS in practice because they usually focus on certain restricted classes of systems. In this article, we present a path-oriented, derivative-free approach to falsify safety properties in nonlinear and nondeterministic CPS. In our approach, we model the behavior of CPS by hybrid automata. Then, we enumerate candidate paths of hybrid automata (HA), transform the feasibility of candidate paths into optimization problems, and solve these optimization problems by our newly proposed classification model-based, derivative-free optimization algorithm. We also provide two novel pruning techniques to further improve the efficiency and efficacy of our approach: 1) a nested optimization structure with better model refinements for continuous search space pruning and 2) a hardly feasible path prefixes guided backtracking for discrete search space pruning. We implement our approach into a tool called PDF. Our experiments showed that PDF supported the safety falsification of CPS in all of our benchmarks, and it achieved success rates no lower than 95% in only seconds on 22/28 of the benchmarks.

Design and Verification of Cyber-Physical Systems Specified by Petri Nets—A Case Study of a Direct Matrix Converter

The paper proposes a novel design technique of cyber-physical systems (CPSs). The system is specified by a Petri net, and further modelled in a hardware description language (HDL) towards final implementation in a programmable device. Contrary to the traditional design methods, the proposed solution is highly focused on the verification aspects. The system is checked three times before the final implementation in hardware. Initially, the Petri-net based specification is formally verified by the application of the model-checking technique. Secondly, software verification of the modelled system is performed. Finally, the hardware verification of the already implemented system is executed. The proposed method is explained by an example of a direct matrix converter (MC) with transistor commutation and space vector modulation (SVM). The main benefits, as well as the limitations, of the proposed solution are discussed and analysed.

Model-based Construction and Verification of Cyber-Physical Systems

By combining communication, computation, and control (3C), Cyber-Physical Systems (CPS)0tightly couple the physical world with the cyber-world, to enable more applications, enhance performance, increase dependability and etc. Among these goals, as CPS are widely used in the safety-critical area, guaranteeing the basic dependability/safety is after all the prerequisite and often the top concern. However, the behavior of CPS is extremely complex. First of all, due to the existence of both discrete control modes transition and continuous real-time behavior in CPS, the behavior of CPS is a complex hybrid state space, which is difficult to understand and handle. Secondly, most CPS applications are working in the open environment and acquiring real-time data from the environment intensively to adjust their own behavior. The dynamic environment makes the behavior space more complex to reason. When a system is too complex to analyze directly, building an abstract model of the system and then conducting analysis on the model to answer questions about the original system is an important and widely-used method. Meanwhile, a reasonable model also plays important roles in the phase of specification, design, development, testing, monitoring and so on. Therefore, it is an important topic of investigating how model-based methods can be applied in the context of CPS to increase the quality and dependability of the system. During the past decade, our research group at Nanjing University has devoted a lot of efforts into this mission. We conducted comprehensive research in a wide spectrum of CPS including model-driven design, verification, control, monitoring, and testing. In this paper, we will make a general review of the progress we made on these directions recently.

A Formal Approach for Modeling and Simulation of Human Car-Following Behavior

Car-following is the activity of safely driving behind a leading vehicle. Traditional mathematical car-following models capture vehicle dynamics without considering human factors, such as driver distraction and the reaction delay. Consequently, the resultant model produces overly safe driving traces during simulation, which are unrealistic. Some recent work incorporate simplistic human factors, though model validation using experimental data is lacking. In this paper, we incorporate three distinct human factors in new compositional car-following model called modal car-following model, which is based on hybrid input output automata (HIOA). HIOA have been widely used for the specification and verification of cyber-physical systems. HIOA incorporate the modeling of the physical system combined with discrete mode switches, which is ideal for describing piece-wise continuous phenomena. Thus, HIOA models offer a succinct framework for the specification of car-following behavior. The human factors considered in our approach are estimation error (due to imperfect distance perception), reaction delay, and temporal anticipation. Two widely used car-following models called Intelligent Driver Model (IDM) and Full Velocity Difference Model (FVDM) are used for extension and comparison purpose. We evaluate the root mean square (rms) error of the following vehicle position using the traces obtained from human drives through different driving scenarios. The result shows that our model reduces the rms error in IDM and FVDM by up to 48.8% and 7.41%, respectively.

A Systematic Mapping Study on the Verification of Cyber-Physical Systems

Cyber-physical system (CPS) is a kind of complex real-time hybrid system which involves deep interactions between computation processors, communication network, and physical environments are deemed as the key enablers of next generation computer applications. However, how to verify CPS effectively is always a great challenge. Based on current scientific works about CPS verification, this paper aims at identifying the gap of current studies and suggesting promising areas for the future works. For this purpose, we conduct a systematic mapping study over the topic on verification of cyber-physical system. We carry out a widely search of publications from 2006 to 2018 in 11 electronic databases. After the step of study selection, 80 papers are selected as primary studies for answering proposed research questions, focused questions, and statistical questions. According to these questions and their answers, this paper not only presents a quantitative and comprehensive analysis of verification challenges, abstraction methods, verification techniques, assistance tools, and verification scenarios that represent each step of verification works, but also summarizes CPS systematic natures, main routine of verification and future research directions. We believe that this survey can identify gaps in current research works and reveal new insights for the future works.

Formal Requirement Debugging for Testing and Verification of Cyber-Physical Systems

A framework for the elicitation and debugging of formal specifications for Cyber-Physical Systems is presented. The elicitation of specifications is handled through a graphical interface. Two debugging algorithms are presented. The first checks for erroneous or incomplete temporal logic specifications without considering the system. The second can be utilized for the analysis of reactive requirements with respect to system test traces. The specification debugging framework is applied on a number of formal specifications collected through a user study. The user study establishes that requirement errors are common and that the debugging framework can resolve many insidious specification errors.

Guest Editorial

Guest Editorial

Real-Time Simulation Support for Runtime Verification of Cyber-Physical Systems

In Cyber-Physical Systems (CPS), cyber and physical components must work seamlessly in tandem. Runtime verification of CPS is essential yet very difficult, due to deployment environments that are expensive, dangerous, or simply impossible to use for verification tasks. A key enabling factor of runtime verification of CPS is the ability to integrate real-time simulations of portions of the CPS into live running systems. We propose a verification approach that allows CPS application developers to opportunistically leverage real-time simulation to support runtime verification. Our approach, termed B race B ind , allows selecting, at runtime, between actual physical processes or simulations of them to support a running CPS application. To build B race B ind , we create a real-time simulation architecture to generate and manage multiple real-time simulation environments based on existing simulation models in a manner that ensures sufficient accuracy for verifying a CPS application. Specifically, B race B ind aims to both improve simulation speed and minimize latency, thereby making it feasible to integrate simulations of physical processes into the running CPS application. B race B ind then integrates this real-time simulation architecture with an existing runtime verification approach that has low computational overhead and high accuracy. This integration uses an aspect-oriented adapter architecture that connects the variables in the cyber portion of the CPS application with either sensors and actuators in the physical world or the automatically generated real-time simulation. Our experimental results show that, with a negligible performance penalty, our approach is both efficient and effective in detecting program errors that are otherwise only detectable in a physical deployment.

Towards Verification of Uncertain Cyber-Physical Systems

Cyber-Physical Systems (CPS) pose new challenges to verification and validation that go beyond the proof of functional correctness based on high-level models. Particular challenges are, in particular for formal methods, its heterogeneity and scalability. For numerical simulation, uncertain behavior can hardly be covered in a comprehensive way which motivates the use of symbolic methods. The paper describes an approach for symbolic simulation-based verification of CPS with uncertainties. We define a symbolic model and representation of uncertain computations: Affine Arithmetic Decision Diagrams. Then we integrate this approach in the SystemC AMS simulator that supports simulation in different models of computation. We demonstrate the approach by analyzing a water-level monitor with uncertainties, self-diagnosis, and error-reactions.

V for Verification: Intelligent Algorithm of Checking Reliability of Smart Systems

Cyber-physical systems (CPS) are intended to receive information from the environment through sensors and perform appropriate actions using actuators of the controller. In the last years world of intelligent technologies has grown in an exponential fashion: from cruise control to smart ecosystems. Next we are facing the future of CPS involved in almost every aspect of our lives bringing higher comfortability and efficiency. Our goal is to help smart inventions adjust to this highly uncertain environment and guarantee safety for its inhabitants. The physical environment renders the problem of CPS verification extremely cumbersome. Due to a wealth of uncertainties introduced by physical processes, the system is best described by stochastic models. Approximate prediction techniques, such as Statistical Model Checking (SMC), have therefore recently become increasingly popular. As a result, verification of a CPS boils down to quantitative analysis of how close the system is to reaching bad states (safety property) or desired goal (liveness property). Controlling the systems, that is, computing appropriate response actions depending on the environment, involves probabilistic state estimation, as well as optimal action prediction, i.e., choosing the best next step by simulating the future. In my thesis, I develop a novel intelligent algorithm addressing existing deficiencies of SMC such as poor prediction of rare events (RE) and sampling divergence.

Perceptions on the State of the Art in Verification and Validation in Cyber-Physical Systems

It is widely held that debugging cyber-physical systems (CPS) is challenging; many strongly held beliefs exist regarding how CPS are currently debugged and tested and the suitability of various techniques. For instance, dissenting opinions exist as to whether formal methods (including static analysis, theorem proving, and model checking) are appropriate in CPS verification and validation. Simulation tools and simulation-based testing are also often considered insufficient for CPS. Many “experts” posit that high-level programming languages (e.g., Java or C#) are not applicable to CPS due to their inability to address (significant) resource constraints at a high level of abstraction. To date, empirical studies investigating these questions have not been done. In this paper, we qualitatively and quantitatively analyze why debugging CPS remains challenging and either dispel or confirm these strongly held beliefs along the way. Specifically, we report on a structured online survey of 25 CPS researchers (10 participants classified themselves as CPS developers), semistructured interviews with nine practitioners across four continents, and a qualitative literature review. We report these results and discuss several implications for research and practice related to CPS.

Design and verification of Cyber-Physical Systems using TrueTime, evolutionary optimization and UPPAAL

Timing imperfections in Cyber-Physical Systems (CPS) components affect their performance and reliability. This investigation presents a methodology to design and verify CPS using multi-objective evolutionary optimization, model checking and supporting software tools. The time-varying delays in CPS are modeled as constant delays plus jitter. It is shown that the CPS design problem is a trade-off between performance and jitter margin. To make good trade-offs, this investigation models the design problem as a constrained multi-objective optimization problem. The design algorithm results in a non-linear and multi-objective optimization problem that is generally difficult to solve. To overcome this computation barrier, this investigation uses the evolutionary algorithm Non-dominated Sorting Genetic Algorithm II (NSGA II). Solution of the optimization problem computes the proportional integral and derivative controller gains that simultaneously maximize the jitter margin while improving the system performance. Implementing the CPS controller in embedded platform requires the selection and validation of the process schedules as well as network protocols. To validate the CPS design, the computed controller gains are simulated in TrueTime to verify the performance for a given network protocol and processor scheduling policy. Three scheduling policies are considered due to their appropriateness for use with temporal imperfections: fixed priority, earliest deadline first and deadline monotonic. Finally, to verify the CPS for timing guarantees, a timed-automata model is used that defines the timing interfaces among the components. The formal model is then used to verify CPS response time and properties such as safety using computation tree logic in UPPAAL model checker. The proposed CPS design and verification approach is illustrated on an industrial mine pump example. Our results demonstrate that the proposed approach can be used to design and validate CPS for performance and verify timing guarantees. The proposed method provides a systematic design and verification approach that can be used for deployments of CPS in industries.

Metrological verification of cyberphysical systems

Metrological verification of cyberphysical systems

Virtual Design and Verification of Cyber-physical Systems: Industrial Process Plant Design

This paper discusses a research project to support virtual design and verification of industrial process plant designs. Process plants are a class of cyber-physical systems (CPS), and these research results should generally apply to other types of CPS such as those associated with the Smart Grid. Modeling is an essential part of process plant design and integral in other applications such as manufacturing. Models produced in design have obvious roles in system implementation, deployment and certification. For manufacturing systems, models also have use in downstream activities including system certification, performance optimization, real-time diagnostics and prognostics, and maintenance. The paper discusses the results associated with a prototype that uses domain-specific models of different views of a system design that improves collaboration through integrated models and aligned semantics and provides examples of how the integration with formal methods can identify defects in designs, and automatically generate test vectors with requirement-to-test traceability.

A logic-based modeling and verification of CPS

Cyber-physical systems (CPS) consist of perpetually and concurrently executing physical and computational components. The presence of physical components require the computational components to deal with continuous quantities. A formalism that can model discrete and continuous quantities together with concurrent, perpetual execution is lacking. In this paper we report on the development of a formalism based on logic programming extended with co-induction, constraints over reals , and coroutining that allows CPS to be elegantly modeled. This logic programming realization can be used for verifying interesting properties as well as generating implementations of CPS. We illustrate this formalism by applying it to elegant modeling of the reactor temperature control system . Interesting properties of the system can be verified merely by posing appropriate queries to this model. Precise parametric analysis can also be performed.

Research directions in energy-sustainable cyber–physical systems

An overview of sustainable computing is provided and different approaches towards design and verification of energy-sustainable computing (i.e., sustainable computing from energy consumption perspective) are discussed for cyber–physical systems (CPSs), i.e., systems with strong coupling between computing components and non-computing processes in physical environment. A major issue in this regard is the inter-dependencies of the non-computing processes on the computing components and vice versa, and the verification of the CPSs’ sustainability without real deployment. The trends and dependencies of energy consumption for both computing and non-computing components are conceptualized. Based on this conceptualization, CPS resource management algorithms are categorized according to: (i) computing workload execution and arrival profiles supported, (ii) knowledge of workload profiles during management decision making, (iii) support of power management in the computing components, and (iv) assumptions on non-computing process behavior. These categories are then discussed along with their pros and cons for two representative CPSs: data centers and body sensor networks (BSNs). A model based engineering approach is used to verify CPS sustainability before real deployment. Several research directions and open problems are further discussed for the design and verification of energy-sustainable CPSs.