Formal Verification Techniques Research Articles

Memoization in Model Checking for Safety Properties with Multi-Swarm Particle Swarm Optimization

In software engineering, errors or faults in software systems often lead to critical social problems. One effective methodology to tackle this problem is model checking, which is an automated formal verification technique. In traditional model checking, the task of finding specification errors is reduced to deterministic search techniques such as Depth-First Search. Recent research has shown that swarm intelligence offers a powerful search capability compared to traditional techniques. In particular, multi-swarm Particle Swarm Optimization is known to be efficient and can mitigate the state-space explosion problem, i.e., the exponential increase in the search space with a linear increase in the problem size. However, the state-space explosion problem is still significant when verifying very large systems. Further performance improvement is needed. To achieve this, we propose a novel memoization or cache mechanism for storing tentative solutions for reuse in the later stages of the search procedure. For each stage, a candidate solution computed by a swarm is summarized efficiently and heuristically to consolidate similar solutions into a single representative solution. We store the summary and its associated solutions in key-value maps. Instead of computing known solutions repeatedly, we retrieve the solution if the stored key matches the summary. We incorporated the proposed mechanism into a model-checking technique with multi-swarm Particle Swarm Optimization and evaluated the search performance. We show in this paper that the proposed mechanism improved time and space consumption while maintaining solution quality.

Advanced Security Auditing Methods for Solidity-Based Smart Contracts

The development of smart contracts remains in its early stages, with significant differences in underlying programming languages and application platforms resulting in a lack of standardization. This lack of standardization increases the susceptibility to vulnerabilities and associated financial losses. To address security vulnerabilities in smart contracts on the Ethereum blockchain platform, this paper proposes a security audit method based on formal verification. The method integrates an input module, static analysis module, formal verification module, analog execution module, and report and recommendation module, which can accurately discover the security vulnerabilities and logical flaws of smart contracts through formal verification and other analysis techniques, thus realizing correctness detection. During the experiment, the method detects 8 types of common vulnerabilities in 148 smart contracts and marks 21 smart contracts with vulnerabilities. After manual review and analysis, it is found that 17 of these 21 marked smart contracts do have security vulnerabilities. The experimental results show that the proposed method can accurately detect security vulnerabilities and logic flaws in smart contracts through formal verification and other analysis techniques before smart contracts are deployed, thus significantly improving the security of smart contracts and reducing the economic losses that may be caused by code defects.

Towards partial monitoring: Never too early to give in

Runtime Verification is a lightweight formal verification technique used to verify whether a system behaves as expected at runtime. Expected behaviour is typically formally specified using properties, which are used to automatically synthesise monitors. Properties that can be verified at runtime by a monitor are called monitorable, while those that cannot are termed non-monitorable. In this paper, we revisit the notion of monitorability and demonstrate how non-monitorable properties can still be used to generate partial monitors. We tackle this from two different perspectives: (i) by recognising that a monitor can give up on monitoring the property under analysis if it recognises that the monitoring will never conclude the satisfaction or violation of the property; (ii) by recognising that a monitor can give up on events that are not necessary for successful monitoring of the property under analysis. By considering these two aspects, we present how to achieve partial monitoring of Linear Temporal Logic properties by building upon the standard monitor construction. Finally, we present a prototype implementation of our approach and its application to a remote inspection case study, as well as a set of evaluation experiments to stress test our approach using synthetic properties.

Formal analysis of an AUTOSAR-based basic software module

The widespread use of advanced driver assistance systems in modern vehicles, together with their integration with the Internet and other road nodes, has made vehicle more vulnerable to cyber-attacks. To address these risks, the automotive industry is increasingly focusing on the development of security solutions: formal methods and software verification techniques, which have been successfully applied to a number of safety-critical systems, could be a promising approach in the automotive area. In this work, we concentrate on in-vehicle communications, provided by many Electronic Control Units (ECUs) that work together thanks to serial protocols such as Controller Area Network (CAN). However, increasing connectivity exposes the internal network to a variety of cyber-risks. Our aim is to formally verify the AUTOSAR-based Basic Software module called CINNAMON, designed to ensure confidentiality, integrity, and authentication at the same time for traffic exchanged over CAN protocol. More precisely, it adds confidentiality guarantees to the Secure Onboard Communication (SecOC) module. We formally analyze CINNAMON with the verification tool Tamarin. Our analysis shows that CINNAMON could be an effective security solution, as it can ensure the desired properties, in particular, confidentiality in a send-receive scenario between two ECUs. Finally, we describe a potential application scenario.

Formal dependability analysis of fault tolerant Virtual Machine allocation strategies in Cloud Radio Access Network

Cloud Radio Access Network (C-RAN) has been proposed as a fifth generation (5G) cellular network that is designed to physically separate the Baseband Units (BBUs) from the Remote Radio Heads (RRHs). The BBUs are placed in the BBU pool/hotel, while the RRHs are located in the cells. This separation enables sharing baseband processing resources among RRHs by generating Virtual Machines (VMs) in the BBU pool, leading to radio coordination and energy saving opportunities. Nevertheless, the failure of a BBU can affect several RRHs, causing outages in the radio network. Therefore, designing a reliable and resilient C-RAN is essential to provide high availability and service continuity in case of BBU failure. This paper deals with using formal verification techniques to analyze the performance and the dependability of C-RAN architecture. We propose fault tolerant VM allocation strategies that can handle BBU failures, thus improving the system’s overall reliability. Based on redundancy techniques, these strategies ensure call recovery through migration to functional BBUs in the case of a BBU failure. In order to evaluate the mutual impact of performance measures on the system’s dependability, we develop performability (combination of performance and dependability) Markov Reward Models (MRMs) for the proposed strategies. We use Probabilistic Model Checking (PMC) to check the performability requirements written with Continuous Stochastic Reward Logic (CSRL). The proposed models are implemented and checked using the PRISM model checker, which supports solving MRMs and checking CSRL properties.

Hardware Model Checking Algorithms and Techniques

Digital systems are nowadays ubiquitous and often comprise an extremely high level of complexity. Guaranteeing the correct behavior of such systems has become an ever more pressing need for manufacturers. The correctness of digital systems can be addressed resorting to formal verification techniques, such as model checking. Currently, it is usually impossible to determine a priori the best algorithm to use given a verification task and, thus, portfolio approaches have become the de facto standard in model checking verification suites. This paper describes the most relevant algorithms and techniques, at the foundations of bit-level SAT-based model checking itself.

Learning to Execute Timed-Temporal-Logic Navigation Tasks under Input Constraints in Obstacle-Cluttered Environments

This study focuses on addressing the problem of motion planning within workspaces cluttered with obstacles while considering temporal and input constraints. These specifications can encapsulate intricate high-level objectives involving both temporal and spatial constraints. The existing literature lacks the ability to fulfill time specifications while simultaneously managing input-saturation constraints. The proposed approach introduces a hybrid three-component control algorithm designed to learn the safe execution of a high-level specification expressed as a timed temporal logic formula across predefined regions of interest in the workspace. The first component encompasses a motion controller enabling secure navigation within the minimum allowable time interval dictated by input constraints, facilitating the abstraction of the robot’s motion as a timed transition system between regions of interest. The second component utilizes formal verification and convex optimization techniques to derive an optimal high-level timed plan over the mentioned transition system, ensuring adherence to the agent’s specification. However, the necessary navigation times and associated costs among regions are initially unknown. Consequently, the algorithm’s third component iteratively adjusts the transition system and computes new plans as the agent navigates, acquiring updated information about required time intervals and associated navigation costs. The effectiveness of the proposed scheme is demonstrated through both simulation and experimental studies.

VConMC: Enabling Consistency Verification for Distributed Systems Using Implementation-Level Model Checkers and Consistency Oracles

Many cloud services are relying on distributed key-value stores such as ZooKeeper, Cassandra, HBase, etc. However, distributed key-value stores are notoriously difficult to design and implement without any mistakes. Because data consistency is the contract for clients that defines what the correct values to read are for a given history of operations under a specific consistency model, consistency violations can confuse client applications by showing invalid values. As a result, serious consequences such as data loss, data corruption, and unexpected behavior of client applications can occur. Software bugs are one of main reasons why consistency violations may occur. Formal verification techniques may be used to make designs correct and minimize the risks of having bugs in the implementation. However, formal verification is not a panacea due to limitations such as the cost of verification, inability to verify existing implementations, and human errors involved. Implementation-level model checking has been heavily explored by researchers for the past decades to formally verify whether the underlying implementation of distributed systems have bugs or not. Nevertheless, previous proposals are limited because their invariant checking is not versatile enough to check for the wide spectrum of consistency models, from eventual consistency to strong consistency. In this work, consistency oracles are employed for consistency invariant checking that can be used by implementation-level model checkers to formally verify data consistency model implementations of distributed key-value stores. To integrate consistency oracles with implementation-level distributed system model checkers, the partial-order information obtained via API is leveraged to avoid the exhaustive search during consistency invariant checking. Our evaluation results show that, by using the proposed method for consistency invariant checking, our prototype model checker, VConMC, can detect consistency violations caused by several real-world software bugs in a well-known distributed key-value store, ZooKeeper.

Stochastic formal model of PI3K/mTOR pathway in Alzheimer's disease for drug repurposing: An evaluation of rapamycin, LY294002, and NVP-BEZ235

Alzheimer's disease is the most common form of dementia characterized by the gradual loss of memory and cognition of patients. There is no drug capable of curing or preventing the disease, being the discovery of an efficient treatment for the disease is of vital importance. An approach that can contribute to this purpose of reducing time and costs of new discoveries is drug repositioning and in silico techniques. Statistical Model Checking is a formal verification technique that can aid in analyzing protein and drugs interactions and test pharmacological strategies, contributing to drug discovery and repurposing. In this work, we present a stochastic formal model that allows us to test different drugs, or combination of drugs, that target the PI3K/mTOR pathway and to evaluate the effect on tau protein and A β peptide, which are two important components that contribute to the progression of Alzheimer's disease. We have analyzed the effect of rapamycin, LY294002, and NVP-BEZ235 on those proteins. Our results have shown that rapamycin has the potential to slow down one of the biological processes that cause neuronal death. Moreover, we have identified the ideal dose of rapamycin to obtain such results. However, our findings have unveiled that LY294002 and NVP-BEZ235 can increase tau phosphorylation in all scenarios tested. This is an alert to the scientific community, as this deleterious effect can be caused by other PI3K inhibitor drugs used to treat different diseases. These results suggest the inhibition of some proteins of the pathway can trigger an unexpected pathology. Besides that, rapamycin has not reduced this side effect when administered together with LY294002. The proposed methodology has been able to model both the disease and drug interactions. We have analyzed three drugs and our model is flexible to test other drugs and pharmacological strategies and efficient to analyze the properties of the model generating new insights.

SPECIFICATION FORMALIZATION OF STATE CHARTS FOR COMPLEX SYSTEM MANAGEMENT

This article presents a formalization approach for the requirements of object-oriented programs with state machines, using a spacecraft control system as a case study. It proposes a state pattern implementation, where each state is represented as a class with clearly defined responsibilities, and the transitions between states are controlled by the state objects themselves. Additionally, the application of model checking, theorem proving, and code generation techniques are discussed. The effectiveness of the proposed approach in ensuring compliance with the specified requirements is demonstrated, while also identifying potential drawbacks and limitations of the approach. The implementation is validated using a range of formal verification techniques, including model checking and theorem proving. The article also discusses how the approach can be extended and applied to other complex systems. Overall, the valuable insights into the formalization of requirements for object-oriented programs with state machines are provided, offering a practical and effective approach for verifying the correctness and completeness of such implementations. The results of this work have important implications for the development of safety-critical systems and can potentially improve the quality and reliability of software systems in various domains. By using mathematical models and rigorous formal methods, it is possible to detect and eliminate errors early in the development process, leading to higher confidence in the correctness of the final product. Future research in this area could explore the use of more advanced techniques, such as model-driven development and automatic code synthesis, to further streamline the software development process. Additionally, the development of more efficient and user-friendly tools could make these techniques more accessible to a wider range of developers and organizations. Altogether, the combination of formal methods and software engineering has the potential to revolutionize the way software systems are designed, developed, and verified, leading to safer and more reliable software for critical applications.

A Survey on Formal Verification and Validation Techniques for Internet of Things

The Internet of Things (IoT) has brought about a new era of connected devices and systems, with applications ranging from healthcare to transportation. However, the reliability and security of these systems are critical concerns that must be addressed to ensure their safe and effective operation. This paper presents a survey of formal verification and validation (FV&V) techniques for IoT systems, with a focus on the challenges and open issues in this field. We provide an overview of formal methods and testing techniques for the IoT and discuss the state explosion problem and techniques to address it. We also examined the use of AI in software testing and describe examples of tools that use AI in this context. Finally, we discuss the challenges and open issues in FV&V for the IoT and present possible future directions for research. This survey paper aimed to provide a comprehensive understanding of the current state of FV&V techniques for IoT systems and to highlight areas for further research and development.

Verifiable biology.

The formalization of biological systems using computational modelling approaches as an alternative to mathematical-based methods has recently received much interest because computational models provide a deeper mechanistic understanding of biological systems. In particular, formal verification, complementary approach to standard computational techniques such as simulation, is used to validate the system correctness and obtain critical information about system behaviour. In this study, we survey the most frequently used computational modelling approaches and formal verification techniques for computational biology. We compare a number of verification tools and software suites used to analyse biological systems and biochemical networks, and to verify a wide range of biological properties. For users who have no expertise in formal verification, we present a novel methodology that allows them to easily apply formal verification techniques to analyse their biological or biochemical system of interest.

Assessing business process models: a literature review on techniques for BPMN testing and formal verification

PurposeTesting business processes is crucial to assess the compliance of business process models with requirements. Automating this task optimizes testing efforts and reduces human error while also providing improvement insights for the business process modeling activity. The primary purposes of this paper are to conduct a literature review of Business Process Model and Notation (BPMN) testing and formal verification and to propose the Business Process Evaluation and Research Framework for Enhancement and Continuous Testing (bPERFECT) framework, which aims to guide business process testing (BPT) research and implementation. Secondary objectives include (1) eliciting the existing types of testing, (2) evaluating their impact on efficiency and (3) assessing the formal verification techniques that complement testing.Design/methodology/approachThe methodology used is based on Kitchenham's (2004) original procedures for conducting systematic literature reviews.FindingsResults of this study indicate that three distinct business process model testing types can be found in the literature: black/gray-box, regression and integration. Testing and verification approaches differ in aspects such as awareness of test data, coverage criteria and auxiliary representations used. However, most solutions pose notable hindrances, such as BPMN element limitations, that lead to limited practicality.Research limitations/implicationsThe databases selected in the review protocol may have excluded relevant studies on this topic. More databases and gray literature could also be considered for inclusion in this review.Originality/valueThree main originality aspects are identified in this study as follows: (1) the classification of process model testing types, (2) the future trends foreseen for BPMN model testing and verification and (3) the bPERFECT framework for testing business processes.

Incrementally predictive runtime verification

Abstract Runtime verification is a lightweight formal verification technique used to verify the runtime behaviour of software (resp. hardware) systems. Given a formal property, one or more monitors are synthesized to verify the latter against a system execution. A monitor can only conclude the violation of a property when it observes such a violation. Unfortunately, in safety-critical scenarios, this might happen too late for the system to react properly. In such scenarios, it is advised to use predictive runtime verification, where monitors are capable of anticipating (by using a model of the system) future events before actually observing them. In this work, instead of assuming such a model is given, we describe a runtime verification workflow where the model is learnt and incrementally refined by using process mining techniques. We present the approach and the resulting prototype tool.

Formal methods to comply with rules of the road in autonomous driving: State of the art and grand challenges

We provide a review of recent work on formal methods for autonomous driving. Formal methods have been traditionally used to specify and verify the behavior of computer programs and digital circuits. Enabled by abstraction techniques for dynamical systems and the availability of verification and synthesis tools for finite systems, they have been adopted by the control and robotics communities. In particular, in autonomous driving, recent research proposes formal languages such as temporal logics to specify driving behaviors ranging from safety, such as collision avoidance, to compliance with complex rules of the road. Our review focuses on formal verification, monitoring, and synthesis techniques enabling autonomous vehicles to adhere to such specifications. We only consider works about system-level methods that have an ego-centric perspective, i.e., we focus on the behavior of an autonomous vehicle in its entirety, rather than specific software code within the vehicle or traffic networks consisting of multiple vehicles. This paper also identifies the main remaining challenges.

Formal Verification of Deep Brain Stimulation Controllers for Parkinson's Disease Treatment.

Deep brain stimulation (DBS) is a widely accepted treatment for the Parkinson's disease (PD). Traditionally, it is done in an open-loop manner, where stimulation is always ON, irrespective of the patient needs. As a consequence, patients can feel some side effects due to the continuous high-frequency stimulation. Closed-loop DBS can address this problem as it allows adjusting stimulation according to the patient need. The selection of open- or closed-loop DBS and an optimal algorithm for closed-loop DBS are some of the main challenges in DBS controller design, and typically the decision is made through sampling based simulations. In this letter, we used model checking, a formal verification technique used to exhaustively explore the complete state space of a system, for analyzing DBS controllers. We analyze the timed automata of the open-loop and closed-loop DBS controllers in response to the basal ganglia (BG) model. Furthermore, we present a formal verification approach for the closed-loop DBS controllers using timed computation tree logic (TCTL) properties, that is, safety, liveness (the property that under certain conditions, some event will eventually occur), and deadlock freeness. We show that the closed-loop DBS significantly outperforms existing open-loop DBS controllers in terms of energy efficiency. Moreover, we formally analyze the closed-loop DBS for energy efficiency and time behavior with two algorithms, the constant update algorithm and the error prediction update algorithm. Our results demonstrate that the closed-loop DBS running the error prediction update algorithm is efficient in terms of time and energy as compared to the constant update algorithm.

A Methodology Framework for Modelling a Rail Moving Block System

In the railway field, rigorous development processes contribute to implement safe and efficient systems. Railway safety standards recommend the use of formal modelling and verification techniques to guarantee processes’ correctness and validate safety requirements. ERTMS/ETCS L3 (European Railway Traffic Management System / European Train Control System Level 3) is a European standard for interoperable railways based on the concept of Moving Block signaling systems which allows for substantial capacity gains and reduced costs. In this paper, we explain why the ETCS L3 struggles to be deployed despite the benefits it can bring. Then, we discuss the planned implementations of ETCS L3 at a European-wide scale. Finally, we present a methodology framework using formal models to verify moving block systems. This work is performed in the context of the PERFORMINGRAIL European project.

Security Analysis of a Digital Twin Framework Using Probabilistic Model Checking

Digital Twins (DTs) have been gaining popularity in various applications, such as smart manufacturing, smart energy, smart mobility, and smart healthcare. In simple terms, DT is described as a virtual replica of a given physical product, system, or process. It consists of three major segments: the physical entity, its virtual counterpart, and the connections between them. While the data is collected from a physical entity, processed at the virtual layer, and accessed in the form of a DT at the application layer, it is exposed to several security risks. To ensure the applicability of a DT system, it is imperative to understand these security risks and their implications. However, there is a lack of a framework that can be used to assess the security of a DT. This paper presents a framework in which the security of a DT can be analyzed with the help of a formal verification technique. The framework captures the defense of the system at different layers and considers various attacks at each layer. The security of the DT system is represented as a state-transition system and the security properties are captured in temporal logic. Probabilistic model checking (PMC) is used to verify the systems against these properties. In particular, the framework is used to analyze the probability of success and the cost of various potential attacks that can occur at each layer in a DT system. The applicability of the proposed framework is demonstrated with the help of a detailed case study in the healthcare domain.

A model-based approach for vulnerability analysis of IoT security protocols: The Z-Wave case study

IoT (Internet of Things) devices are extensively used in security-critical services, as for example home door opening, gas monitoring, alarm systems, etc. Often, they use communication protocols with no standardisation and no security guarantee. Unsecured use of connected devices can cause threats or damages to the users, so security assurance, which can be ensured by the use of formal methods, must be guaranteed. Unfortunately practical usage of formal methods during the protocol design is very limited or missing at all.To address the problem of providing the designer with a user-friendly but rigorous design approach based on the use of formal methods, supporting security assurance already at the model level, but hiding the complexity of formal notations and verification techniques, in this paper we propose an approach, based on the Abstract State Machine formal method, for the specification and verification of security protocols. Specifically, we introduce a set of built-in primitives to model communication protocols and their security properties. Security verification can be carried out under the hypothesis of either a passive or an active attacker.The effectiveness of this approach is shown by means of its application to the Z-Wave protocol, claimed to be one of the most secure protocol for IoT devices communication thanks to the addition of the S2 Security class. We show the formal specification of the Z-Wave protocol and the security verification process.

Model-Driven Development of Service Robot Applications Dealing With Uncertain Human Behavior

In the future, robots will interact with humans in highly variable and unpredictable settings, such as healthcare and home assistance. Frameworks are, therefore, fundamental to analyze and develop interactive robotic applications that can deal by design with the uncertainty of human behavioral and physiological features. Our framework is built upon formal modeling, verification, and learning techniques providing sound mathematical guarantees of human wellbeing preservation throughout the interaction and timely mission completion despite the uncertainties at play. The framework’s workflow makes it accessible to professional figures without expertise in formal methods, and the high degree of automation minimizes the manual effort required throughout the toolchain. The development of toolchain has been tested on use cases from the healthcare setting, in which human behavior is unconstrained, and subjects are often in critical mental or physical conditions.