Model-checking Algorithm Research Articles

Generalized possibility computation tree logic with frequency and its model checking

In recent years, there has been significant research in the field of possibilistic temporal logic. However, existing works have not yet addressed the issue of frequency, which is a common form of uncertainty in the real world. This article aims to fill this gap by incorporating frequency information into possibilistic temporal logic and focusing on the model-checking problem of generalized possibility computation tree logic (GPoCTL) with frequency information. Specifically, we introduce generalized possibility computation tree logic with frequency (GPoCTLF). Although its syntax can be considered as an extension of frequency constraints of the always operator (□) in GPoCTL, they are fundamentally different in semantics and model-checking methods. To facilitate this extension, useful frequency words such as “always”, “usually”, “often”, “sometimes”, “occasionally”, “rarely”, “hardly ever” and “never” are defined as fuzzy frequency operators in this article. Therefore, this article focuses on investigating the model-checking problem of the frequency-constrained always operator. In addition, we analyze the relationship between some GPoCTLF path formulas and GPoCTL path formulas. Then, we provide a model-checking algorithm for GPoCTLF and analyze its time complexity. Finally, an example of a social network is used to illustrate the calculation process of the proposed method and its potential applications.

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.

Model checking fuzzy computation tree logic of multi-agent systems based on fuzzy interpreted systems

Effective communication among autonomous agents is crucial for coordination and solving complex tasks within multi-agent systems. To formalize interactions between agents, social accessibility relations are often utilized. Current research employs model checking algorithms to verificate social commitment properties in multi-agent systems. In fuzzy multi-agent systems, direct quantification and computation of commitment attributes pose challenges. This paper introduces an indirect fuzzy model checking algorithm designed to convert social commitments in uncertain scenarios into quantifiable attributes for verification. Firstly, we propose a fuzzy communicative interpreted system model to represent multi-agent systems with uncertain communication. We then improve fuzzy computation tree logic by adding modalities for commitments and fulfillment, resulting in a fuzzy computation tree logic with commitments for describing system properties related to commitments. A fuzzy model checking algorithm is subsequently presented. This algorithm converts the task of model checking fuzzy computation tree logic with commitments based on fuzzy interpreted systems into model checking fuzzy computation tree logic based on fuzzy Kripke structures. We conclude by providing proofs of correctness and complexity analysis of our algorithm. Furthermore, we demonstrate the effectiveness of our approach for model checking social commitments under fuzzy conditions through simulation experiments on an online shopping system.

On Alternating-Time Temporal Logic, Hyperproperties, and Strategy Sharing

Alternating-time temporal logic (ATL*) is a well-established framework for formal reasoning about multi-agent systems. However, while ATL* can reason about the strategic ability of agents (e.g., some coalition A can ensure that a goal is reached eventually), we cannot compare multiple strategic interactions, nor can we require multiple agents to follow the same strategy. For example, we cannot state that coalition A can reach a goal sooner (or more often) than some other coalition A'. In this paper, we propose HyperATL*_S, an extension of ATL* in which we can (1) compare the outcome of multiple strategic interactions w.r.t. a hyperproperty, i.e., a property that refers to multiple paths at the same time, and (2) enforce that some agents share the same strategy. We show that HyperATL*_S is a rich specification language that captures important AI-related properties that were out of reach of existing logics. We prove that model checking of HyperATL*_S on concurrent game structures is decidable. We implement our model-checking algorithm in a tool we call HyMASMC and evaluate it on a range of benchmarks.

Lazy model checking for recursive state machines

Recursive state machines (RSMs) are state-based models for procedural programs with wide-ranging applications in program verification and interprocedural analysis. Model-checking algorithms for RSMs and related formalisms have been intensively studied in the literature. In this article, we devise a new model-checking algorithm for RSMs and requirements in computation tree logic (CTL) that exploits the compositional structure of RSMs by ternary model checking in combination with a lazy evaluation scheme. Specifically, a procedural component is only analyzed in those cases in which it might influence the satisfaction of the CTL requirement. We implemented our model-checking algorithms and evaluate them on randomized scalability benchmarks and on an interprocedural data-flow analysis of Java programs, showing both practical applicability and significant speedups in comparison to state-of-the-art model-checking tools for procedural programs.

Formal Modelling and Verification of Probabilistic Resource Bounded Agents

Many problems in Multi-Agent Systems (MASs) research are formulated in terms of the abilities of a coalition of agents. Existing approaches to reasoning about coalitional ability are usually focused on games or transition systems, which are described in terms of states and actions. Such approaches however often neglect a key feature of multi-agent systems, namely that the actions of the agents require resources. In this paper, we describe a logic for reasoning about coalitional ability under resource constraints in the probabilistic setting. We extend Resource-bounded Alternating-time Temporal Logic (RB-ATL) with probabilistic reasoning and provide a standard algorithm for the model-checking problem of the resulting logic Probabilistic resource-bounded ATL (pRB-ATL). We implement model-checking algorithms and present experimental results using simple multi-agent model-checking problems of increasing complexity.

Model Checking of Possibilistic Linear-Time Properties Based on Generalized Possibilistic Decision Processes

Model checking possibilistic linear-time properties was investigated by Li (2017). However, nondeterminism of the system is absent in previous studies. Therefore, in order to permit both possibilistic and nondeterministic choices, we use the generalized possibilistic decision process (GPDP) as a model of the system. First, the definition of GPDP describing the behavior of nondeterministic system is given in detail, the resolution of nondeterminism is performed by using the notion of schedulers, and the semantics of generalized possibilistic linear-temporal logic (GPoLTL) with schedulers are defined. Second, we study possibilistic model checking of some fuzzy linear-time properties under GPDP. Since there are many (infinite) schedulers satisfying a certain linear timing property in a given state of a GPDP, it is particularly critical to study the optimal strategy and its corresponding possible measure, which is called extremal possibility model checking. For some special fuzzy linear-time properties, such as constrained reachability, step-bounded constrained reachability, reachability, always reachability, repeated reachability, persistence reachability, we present complete solution to the optimal (including maximum and minimum cases) possibilistic model checking of the above reachability using the fixpoint techniques. We also introduce fuzzy !-regular properties in GPDP and show that their model checking can be simplified by repeated reachability. The algorithms for model checking are also provided. Additionally, an example is presented to illustrate the methods described in the paper.

Detecting bots with temporal logic

Social bots are computer programs that act like human users on social media platforms. Social bot detection is a rapidly growing field dominated by machine learning approaches. In this paper, we propose a complementary method to machine learning by exploring bot detection as a model checking problem. We introduce Temporal Network Logic (TNL) which we use to specify social networks where agents can post and follow each other. Using this logic, we formalize different types of social bot behavior with formulas that are satisfied in a model of a network with bots. We also consider an extension of the logic where we explore the expressive power of including elements from hybrid logic in our framework. We give model checking algorithms for TNL and its hybrid extension, and show that the complexity of the former is in p and the latter in pspace.

Learning-Based Testing Using SAL (Symbolic Analysis Laboratory) Model Checker

This paper studies learning-based testing (LBT) for reactive systems with different learning algorithms and model checkers. LBT is a technique that requires a learning algorithm to learn the models to generate test cases automatically. We have used the generic methodology of LBT to test reactive systems with two different model inference algorithms (i.e., IKL, DKL) and two different model checking tools (i.e., NuSMV, SAL). To investigate the feasibility of LBT, we integrated our SUTs with these algorithms in LBT and tested if LBT optimizes test generation with these algorithms. We tested our SUTs with Boolean data types to check the difference in the working of model inference and model checking algorithms which we analyzed experimentally. The results show that LBT works better with DKL and SAL. DKL is a recently proposed model inference algorithm, and SAL is the latest model checker on which the research is being carried out. DKL and SAL algorithms explore errors in reactive SUTs with the h LBT framework more quickly and efficiently.

From Width-Based Model Checking to Width-Based Automated Theorem Proving

In the field of parameterized complexity theory, the study of graph width measures has been intimately connected with the development of width-based model checking algorithms for combinatorial properties on graphs. In this work, we introduce a general framework to convert a large class of width-based model-checking algorithms into algorithms that can be used to test the validity of graph-theoretic conjectures on classes of graphs of bounded width. Our framework is modular and can be applied with respect to several well-studied width measures for graphs, including treewidth and cliquewidth. As a quantitative application of our framework, we prove analytically that for several long-standing graph-theoretic conjectures, there exists an algorithm that takes a number k as input and correctly determines in time double-exponential in a polynomial of k whether the conjecture is valid on all graphs of treewidth at most k. These upper bounds, which may be regarded as upper-bounds on the size of proofs/disproofs for these conjectures on the class of graphs of treewidth at most k, improve significantly on theoretical upper bounds obtained using previously available techniques.

Imprecise Probabilistic Model Checking for Stochastic Multi-agent Systems

Standard techniques for model checking stochastic multi-agent systems usually assume the transition probabilities describing the system dynamics to be stationary and completely specified. As a consequence, neither non-stationary systems nor systems whose stochastic behaviour is partially unknown can be treated. So far, most of the approaches proposed to overcome this limitation suffer from complexity issues making them poorly efficient in the case of large state spaces. A fruitful but poorly explored way out is offered by the formalism of imprecise probabilities and the related imprecise Markov models. The aim of this paper is to show how imprecise probabilities can be fruitfully involved to model-check multi-agent systems characterised by non-stationary behaviours. Specifically, the paper introduces a new class of multi-agent models called Imprecise Probabilistic Interpreted Systems and their relative extensions with rewards. It also introduces a proper logical language to specify properties of such models and corresponding model checking algorithms based on iterative procedures to compute probabilistic and epistemic inferences over imprecise Markov models.

Reasoning about Quality and Fuzziness of Strategic Behaviors

Temporal logics are extensively used for the specification of on-going behaviors of computer systems. Two significant developments in this area are the extension of traditional temporal logics with modalities that enable the specification of on-going strategic behaviors in multi-agent systems, and the transition of temporal logics to a quantitative setting, where different satisfaction values enable the specifier to formalize concepts such as certainty or quality. In the first class, SL ( Strategy Logic ) is one of the most natural and expressive logics describing strategic behaviors. In the second class, a notable logic is LTL[ℱ] , which extends LTL with quality operators . In this work, we introduce and study SL[ℱ] , which enables the specification of quantitative strategic behaviors. The satisfaction value of an SL[ℱ] formula is a real value in [0,1], reflecting “how much” or “how well” the strategic on-going objectives of the underlying agents are satisfied. We demonstrate the applications of SL[ℱ] in quantitative reasoning about multi-agent systems, showing how it can express and measure concepts like stability in multi-agent systems, and how it generalizes some fuzzy temporal logics. We also provide a model-checking algorithm for SL[ℱ] , based on a quantitative extension of Quantified CTL ⋆ . Our algorithm provides the first decidability result for a quantitative extension of Strategy Logic. In addition, it can be used for synthesizing strategies that maximize the quality of the systems’ behavior.

Logics and Algorithms for Hyperproperties

System requirements related to concepts like information flow, knowledge, and robustness cannot be judged in terms of individual system executions, but rather require an analysis of the relationship between multiple executions. Such requirements belong to the class of hyperproperties, which generalize classic trace properties to properties of sets of traces. During the past decade, a range of new specification logics has been introduced with the goal of providing a unified theory for reasoning about hyperproperties. This paper gives an overview on the current landscape of logics for the specification of hyperproperties and on algorithms for satisfiability checking, model checking, monitoring, and synthesis.

Implementation of a Model-Oriented Approach for Supporting Safe Integration of GNSS-Based Virtual Balises in ERTMS/ETCS Level 3

Moving Block is a railway signaling concept that paves the way for increasing line capacity while reducing maintenance and operating costs. Its implementation relies on autonomous solutions for train localization, mainly based on GNSS technology. However, the introduction of such technological innovations leads to the emergence of new risks. These risks need to be investigated meticulously, and some confidence level needs to be assigned to GNSS-based localization solutions in railways while considering various settings. The contribution of this paper falls within this context by bringing formal approaches into play in order to evaluate performance and safety properties related to the use of GNSS-based virtual balises for train localization. Specifically, the adopted model-based approach consists in translating the relevant behavior of the localization system through configurable timed and probabilistic automata. The elaborated models being parameterizable, various test scenarios, considering a wide range of configurations, can be investigated. Quantitative and qualitative analysis results can be generated on the basis of our models by means of statistical model-checking algorithms implemented in the UPPAAL-SMC modeling and verification tool. A case study is used to illustrate the application of the presented approach, and various numerical analysis results are provided. As the present contribution implements a model-driven approach to perform safety analysis in railways, it is fully in line with the increasing willingness to reduce recourse to on-site tests in the sector. Such tests are indeed costly and time-consuming, thus jeopardizing the introduction of technical innovations in railways.

Construction and Analysis of Petri Net Model for Distributed Cyber Physical Systems

A Distributed Cyber-Physical System (DCPS) composition poses challenges in determining its emergent behaviour. These challenges occur due to (1) the appearance of causal loops of information and energy flow through cyber and physical channels and (2) inherent non-determinism in the temporally ordered flow of events within independently evolving interacting processes of Constituent Systems (CSs). Hence, there is a need to construct a model of the envisaged schematic of DCPS composition for analysis and verification of its significant properties in the conceptual design stage of the system development life cycle.
 This paper presents a procedure to construct DCPS composition models in Petri net formalism using distributed abstractions. The model for each CS is obtained from elementary constructs using compositional operators. The interaction among CSs occurs through channels obtained by connecting send and receive constructs of two CSs participating in an interaction. The internal processing within a CS characterizing its primary function is abstracted in a generic passthrough construct. Representing these constructs with compositional operators results in the complete DCPS model in Petri net formalism. A toolchain with Reference net workshop (Renew) as an integrated Petri net editing and analysis platform is configured to support DCPS modelling, simulation and analysis. The Renew tool functionality has been enhanced with a plugin designed and developed by authors to facilitate the drawing of the distributed composition model.
 A low-level Petri net analysis (Lola) v2.0 plugin is employed to verify the Petri net and temporal properties of the modelled DCPS scenarios. The properties of the resultant model are verified using well-established algorithms to analyze Petri nets. Further, system properties specified using temporal logic can be verified using model-checking algorithms for Petri nets. A moderately complex scenario involving interactions among six CSs illustrates the presented approach.

Model checking differentially private properties

With the explosion of digital data collected from social apps, privacy protection regulations have been issued by almost all countries. Differential privacy is proposed as a successful technique to make use of these data, without leaking personal private data at the same time. In this paper, we investigate logical reasoning for differential privacy properties and propose model checking algorithms. We introduce the branching time temporal logic dpCTL* to specify differentially private properties. Several mechanisms in differential privacy are formalized as Markov chains or Markov decision processes. In our framework, we show that subtle privacy conditions are specified by dpCTL*. In order to verify privacy properties automatically, model checking problems are investigated. We develop a model checking algorithm for Markov chains. Model checking dpCTL* properties on Markov decision processes however is shown to be undecidable. Therefore, we propose a sound algorithm to verify these properties in Markov decision processes. We implement our model checking algorithm into a tool, based on the PRISM language, as well as show the experimental results and a case study of stream processing in differential privacy under the essential fairness assumptions.

Copying safety and liveness properties of computational artefacts

Abstract This paper shows how safety and liveness properties are not necessarily preserved by different kinds of copies of computational artefacts and proposes procedures to preserve them, which are consistent with ethical analyses on software property rights infringement. Safety and liveness are second-order properties that are crucial in the definition of the formal ontology of computational artefacts. Software copies are analysed at the level of their formal models as exact, inexact and approximate copies, according to the taxonomy in [3]. First, it is explained how exact copies are the only kind of copies that preserve safety and liveness properties, and how inexact and approximate copies do not necessarily preserve them. Secondly, two model checking algorithms are proposed to verify whether inexact and approximate copies actually preserve safety and liveness properties. Essential properties of termination, correctness and complexity are proved for these algorithms. Finally, contraction and expansion algorithmic operations are defined, allowing for the automatic design of safety- and liveness-preserving approximate copies. As a conclusion, the relevance of the present logical analysis for the ongoing debates in miscomputation and computer ethics is highlighted.

ATLDesigner: ATL Model Checking Using An Attribute Grammar

In this paper, we use attribute grammars as a formal approach for model checkers development. Our aim is to design an Alternating-Time Temporal Logic (ATL) model checker from a context-free grammar which generates the language of the ATL formulae. An attribute grammar may be informally defined as a context-free grammar which is extended with a set of attributes and a collection of semantic rules. We provide a formal definition for an attribute grammar used as input for Another Tool for Language Recognition (ANTLR) to generate an ATL model checker. The original implementation of the model-checking algorithm is based on Relational Databases and Web Services. Several database systems and Web Services technologies were used for evaluating the system performance in verification of large ATL models.

Bounded model checking distributed temporal logic

Abstract The distributed temporal logic (DTL) is a logic for reasoning about temporal properties of distributed systems from the local point of view of the system’s agents, which are assumed to execute sequentially and to interact by means of synchronous event sharing. Different versions of DTL have been proposed over the years for a number of different applications, reflecting different perspectives on how non-local information can be accessed by each agent. In a recent paper, an automata-theoretic approach to model check DTL was proposed Subtil et al. (2020, Technical Report). Herein, we follow a different approach and adapt the bounded model-checking (BMC) algorithm for linear temporal logic to the case of DTL (see Biere et al. (2003, Adv. Comput., 58, 117–148) and Biere et al. (1999, TACAS 1999, 193–207)). For that purpose, a new notion of bounded semantics for DTL is proposed. In the BMC approach, the witness problem is translated to the satisfiability of a propositional formula that can be addressed (efficiently) by SAT solvers. An important application for this approach is verification of security protocols (Basin et al. (2011, Theoret. Comput. Sci., 412, 4007–4043); Caleiro et al. (2005, Electron. Notes Theor. Comput. Sci., 125, 67–89)).

Characterization, verification and generation of strategies in games with resource constraints

With an increasing demand for ensuring the reliability and efficiency of distributed and interactive systems, the model-checking technique has been studied extensively, for which a game-based modeling of the system and a logical specification of the desired properties are two essential parts. Existing studies mainly focused on ideal systems that always guarantee optimal responses and have not considered several realistic aspects, for instance, the fact that actions can only be performed under sufficient resources. In this paper, we propose a game model with resource constraints and thereby a novel logic named LRC for such games. This logic enables the strategic reasoning of the likely strategies of the other participating entities and thus supports not only the characterization of the equilibrium of games with limited resources, but also strategic exploitation in multi-agent systems in which the available resources are restricted. Interesting properties of this logic are investigated, and a model-checking algorithm is presented. Being built upon the alternating-time temporal logic (ATL), LRC is shown to be more expressive than ATL without bringing additional complexity. In addition to determining the existence or absence of a collaborative strategy, we explore the generation of the team plan when a certain protocol is supposed to be followed.