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Marjan Sirjani

Publications and source records attributed to Marjan Sirjani.

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Modelling and Model-Checking a ROS2 Multi-Robot System using Timed Rebeca

Model-based development accelerates prototyping, enables earlier experimentation, and ensures rigorous validation of system design intents. In multi-agent systems with complex asynchronous interactions and concurrency, formal verification, particularly model-checking, offers an automated means of confirming that desired properties hold. Timed Rebeca, an actor-based modelling language supporting reactive, concurrent, and timed behaviors, together with its model-checking tool, provides a powerful framework for this purpose. By leveraging these capabilities, Timed Rebeca can intuitively capture ROS2 node graphs, recurring physical signals, motion primitives, and other time-convertible behaviors. Nevertheless, modelling and verifying multi-robot systems entail significant challenges: abstracting intricate information, bridging the gap between discrete models and continuous system dynamics, and managing large state spaces while preserving fidelity. To address these challenges, we propose discretization strategies tailored to various data types and identify thresholds of abstraction that balance accuracy and tractability. We further introduce optimization techniques to accelerate verification. Our work demonstrates how to systematically design and verify multi-robot systems through Timed Rebeca, efficiently transform continuous dynamics into discrete models for model-checking, and maintain a practical, bidirectional flow between the abstract model and the ROS2 implementation. The accompanying Rebeca and ROS2 codebases, made openly available, serve as a foundational reference for researchers and developers aiming to model and verify advanced autonomous robotic systems.

cs.RO

Behavioral Analysis of Timed Actors using Syntactic Slice Equivalence

Tiny twins are compact behavioral models derived from timed actor models for selected observable messages. When a source model evolves, regenerating its tiny twin requires state-space exploration and reduction even if the relevant behavior is unchanged. We present a static analysis for Timed Rebeca that compares backward slices of Rebeca dependence graphs for a given set of observable message names. For the Zeno-free fragment with after annotations and no delay statements, we prove that slice equivalence implies weak timed bisimulation under the selected observations. This preserves observable actions and total elapsed time across internal transitions, allowing the existing tiny twin to be reused. We evaluate the implementation on ten benchmark models paired with revisions that preserve their observable slices. The cost of static comparison depends on the size of the graphs representing source statements and their dependencies, while tiny-twin generation depends on the number of reachable states and transitions. This difference is reflected in the measurements: static comparison takes less than one second using tens of megabytes of memory, while tiny-twin generation can take over an hour and use hundreds of gigabytes.

cs.PL

From Automata Learning to Model Checking: Formal Security Verification of Black-Box Protocols

Security verification of communication protocols in industrial and safety-critical systems is challenging because implementations are often proprietary, accessible only as black boxes, and too complex for manual modeling. As a result, existing security testing approaches usually depend on incomplete test suites and/or require labor-intensive modeling, limiting coverage, scalability, and trust. This paper addresses the problem of systematically verifying protocol security properties without access to internal system models. We propose a flexible and scalable method for formal verification of communication protocols that combines active automata learning with model checking to enable rigorous security analysis of black-box protocol implementations. Behavioral models are first inferred from system interactions using automata learning. We then propose context-based proposition maps (CPMs) to enrich the learned models with semantic information, yielding annotated Mealy machines that bridge the gap between learned behavior and property verification. These machines are automatically transformed into verifiable models in the Rebeca modeling language, enabling model checking of generic security properties such as authentication, confidentiality, privilege levels, and key validity, while allowing protocol-specific properties to be manually added. The CPMs are also used to populate these generic properties with protocol-specific propositions. Furthermore, the resulting model can be easily altered to introduce non-deterministic behavior (like timeouts or faults) and examined if the properties still hold under these different conditions. As a result, we gain an automated tool chain that spans from model learning to security property checking of specific protocols.

cs.CR

M, Toolchain and Language for Reusable Model Compilation

Complex software-driven systems often interleave distributed, concurrent computation processes with physical interactions with the environment. Developing these systems more efficiently and safely can be achieved by employing actionable, software-based models. From a high-level system model, engineers often need to derive multiple specialized models for different purposes, including simulation, deployment, and formal verification. Each of these target models usually rely on its own formalism, specification language, and execution platform. Traditionally, a compiler analyzes a program written in a programming language and generates executable code. In contrast, a model compiler processes a source model written in a modeling language and should ideally support the generation of multiple heterogeneous targets. However, most existing modeling languages are designed with a narrow focus, typically targeting only simulation or implementation. Multi-target compilation, when not considered during the language's early design, becomes significantly harder to achieve. In this paper, we introduce our initiative: a toolchain and modeling language called M, designed to support system modeling and multi-target compilation for model-driven engineering of complex, concurrent, and time-aware systems. M is a textual, grammar-driven language based on the actor model and extended with discrete-event scheduling semantics. It provides constructs for modeling system entities, message-based interactions, and time- or state-triggered reactions. From such models, M enables the systematic generation of diverse target artifacts while preserving semantic conformance to the original model. Moreover, M can serve as a middle language to which other modeling languages may anchor, thereby allowing them to benefit from its compilation framework.

cs.SE

LLM-based Property-based Test Generation for Guardrailing Cyber-Physical Systems

Cyber-physical systems (CPSs) are complex systems that integrate physical, computational, and communication subsystems. The heterogeneous nature of these systems makes their safety assurance challenging. In this paper, we propose a novel automated approach for guardrailing cyber-physical systems using property-based tests (PBTs) generated by Large Language Models (LLMs). Our approach employs an LLM to extract properties from the code and documentation of CPSs. Next, we use the LLM to generate PBTs that verify the extracted properties on the CPS. The generated PBTs have two uses. First, they are used to test the CPS before it is deployed, i.e., at design time. Secondly, these PBTs can be used after deployment, i.e., at run time, to monitor the behavior of the system and guardrail it against unsafe states. We implement our approach in ChekProp and conduct preliminary experiments to evaluate the generated PBTs in terms of their relevance (how well they match manually crafted properties), executability (how many run with minimal manual modification), and effectiveness (coverage of the input space partitions). The results of our experiments and evaluation demonstrate a promising path forward for creating guardrails for CPSs using LLM-generated property-based tests.

cs.SE

Hybrid Rebeca Revisited

Hybrid Rebeca is a modeling framework for asynchronous event-based cyber-physical systems (CPSs). In this work, we extend Hybrid Rebeca to allow the modeling of non-deterministic time behavior. Besides the syntactical extension, we formalize the semantics of the extended language in terms of Timed Transition Systems, and adapt a reachability analysis algorithm originally designed for hybrid automata to be applicable to Hybrid Rebeca models. We prove the soundness of our approach and illustrate its applicability on a case study. The case study demonstrates that our dedicated algorithm is clearly superior to the alternative approach of transforming Hybrid Rebeca models to hybrid automata as an intermediate model and then applying the original reachability analysis method to this intermediate transformed models.

cs.FL

Formal Verification of Consistency for Systems with Redundant Controllers

A potential problem that may arise in the domain of distributed control systems is the existence of more than one primary controller in redundancy plans that may lead to inconsistency. An algorithm called NRP FD is proposed to solve this issue by prioritizing consistency over availability. In this paper, we demonstrate how by using modeling and formal verification, we discovered an issue in NRP FD where we may have two primary controllers at the same time. We then provide a solution to mitigate the identified issue, thereby enhancing the robustness and reliability of such systems.

cs.SE

ConstScene: Dataset and Model for Advancing Robust Semantic Segmentation in Construction Environments

The increasing demand for autonomous machines in construction environments necessitates the development of robust object detection algorithms that can perform effectively across various weather and environmental conditions. This paper introduces a new semantic segmentation dataset specifically tailored for construction sites, taking into account the diverse challenges posed by adverse weather and environmental conditions. The dataset is designed to enhance the training and evaluation of object detection models, fostering their adaptability and reliability in real-world construction applications. Our dataset comprises annotated images captured under a wide range of different weather conditions, including but not limited to sunny days, rainy periods, foggy atmospheres, and low-light situations. Additionally, environmental factors such as the existence of dirt/mud on the camera lens are integrated into the dataset through actual captures and synthetic generation to simulate the complex conditions prevalent in construction sites. We also generate synthetic images of the annotations including precise semantic segmentation masks for various objects commonly found in construction environments, such as wheel loader machines, personnel, cars, and structural elements. To demonstrate the dataset's utility, we evaluate state-of-the-art object detection algorithms on our proposed benchmark. The results highlight the dataset's success in adversarial training models across diverse conditions, showcasing its efficacy compared to existing datasets that lack such environmental variability.

cs.CV

Timed Actors and Their Formal Verification

In this paper we review the actor-based language, Timed Rebeca, with a focus on its formal semantics and formal verification techniques. Timed Rebeca can be used to model systems consisting of encapsulated components which communicate by asynchronous message passing. Messages are put in the message buffer of the receiver actor and can be seen as events. Components react to these messages/events and execute the corresponding message/event handler. Real-time features, like computation delay, network delay and periodic behavior, can be modeled in the language. We explain how both Floating-Time Transition System (FTTS) and common Timed Transition System (TTS) can be used as the semantics of such models and the basis for model checking. We use FTTS when we are interested in event-based properties, and it helps in state space reduction. For checking the properties based on the value of variables at certain point in time, we use the TTS semantics. The model checking toolset supports schedulability analysis, deadlock and queue-overflow check, and assertion based verification of Timed Rebeca models. TCTL model checking based on TTS is also possible but is not integrated in the tool.

cs.PL

Specification and Verification of Timing Properties in Interoperable Medical Systems

To support the dynamic composition of various devices/apps into a medical system at point-of-care, a set of communication patterns to describe the communication needs of devices has been proposed. To address timing requirements, each pattern breaks common timing properties into finer ones that can be enforced locally by the components. Common timing requirements for the underlying communication substrate are derived from these local properties. The local properties of devices are assured by the vendors at the development time. Although organizations procure devices that are compatible in terms of their local properties and middleware, they may not operate as desired. The latency of the organization network interacts with the local properties of devices. To validate the interaction among the timing properties of components and the network, we formally specify such systems in Timed Rebeca. We use model checking to verify the derived timing requirements of the communication substrate in terms of the network and device models. We provide a set of templates as a guideline to specify medical systems in terms of the formal model of patterns. A composite medical system using several devices is subject to state-space explosion. We extend the reduction technique of Timed Rebeca based on the static properties of patterns. We prove that our reduction is sound and show the applicability of our approach in reducing the state space by modeling two clinical scenarios made of several instances of patterns.

cs.LO

Schedulability Analysis of WSAN Applications: Outperformance of A Model Checking Approach

Wireless sensor and actuator networks (WSAN) are real-time systems which demand high degrees of reliability requirements. To ensure this level of reliability, different analysis approaches have been proposed for WSAN applications. Among different alternatives, analytical analysis and model checking are two common approaches which are widely used for the formal analysis of WSAN applications. Analytical approaches apply constraint satisfaction methods, whereas model checking generates explicit states of models and analyze them. In this paper, we compare the two approaches in schedulability analysis of WSAN applications using an application for monitoring and control of civil infrastructures, which is implemented on the Imote2 wireless sensor platform. We show how the highest possible data acquisition frequency for this application is computed while meeting the deadlines, and compare the results of the two approaches as well as their scalability, extensibility, and flexibility.

cs.NI

Magnifier: A Compositional Analysis Approach for Autonomous Traffic Control

Autonomous traffic control systems are large-scale systems with critical goals. Due to the dynamic nature of the surrounding world of these systems, assuring the satisfaction of their properties at runtime and in the presence of a change is important. A prominent approach to assure the correct behavior of these systems is verification at runtime, which has strict time and memory limitations. To tackle these limitations, we propose Magnifier, an iterative, incremental, and compositional verification approach that operates on a component-based model. The Magnifier idea is zooming on the component affected by a change, verifying the correctness of properties of interest of the system after adapting the component to the change, and then zooming out and tracing the change if it propagates. If the change propagates, all components affected by the change are adapted and are composed to form a new component. Magnifier repeats the same process for the new component. This iterative process terminates whenever the propagation of the change stops. In Magnifier, we use the Coordinated Adaptive Actor model (CoodAA) of traffic control systems. We present a formal semantics for CoodAA as a network of Timed Input-Output Automata (TIOAs). The change does not propagate if TIOAs of the adapted component and its environment are compatible. We implement our approach in Ptolemy II. The results of our experiments indicate that the proposed approach improves the verification time and the memory consumption compared to a non-compositional approach.

cs.SE

VeriVANca: An Actor-Based Framework for Formal Verification of Warning Message Dissemination Schemes in VANETs

One of the applications of vehicular ad-hoc networks is warning message dissemination among vehicles in dangerous situations to prevent more damage. The only communication mechanism for message dissemination is multi-hop broadcast; in which, forwarding a received message have to be regulated using a scheme regarding the selection of forwarding nodes. When analyzing these schemes, simulation-based frameworks fail to provide guaranteed analysis results due to the high level of concurrency in this application. Therefore, there is a need to use model checking approaches for achieving reliable results. In this paper, we have developed a framework called VeriVANca, to provide model checking facilities for the analysis of warning message dissemination schemes in VANETs. To this end, an actor-based modeling language, Rebeca, is used which is equipped with a variety of model checking engines. To illustrate the applicability of VeriVANca, modeling and analysis of two warning message dissemination schemes are presented. Some scenarios for these schemes are presented to show that concurrent behaviors of the system components may cause uncertainty in both behavior and performance which may not be detected by simulation-based techniques. Furthermore, the scalability of VeriVANca is examined by analyzing a middle-sized model.

cs.NI

Hybrid Rebeca: Modeling and Analyzing of Cyber-Physical Systems

In cyber-physical systems like automotive systems, there are components like sensors, actuators, and controllers that communicate asynchronously with each other. The computational model of actor supports modeling distributed asynchronously communicating systems. We propose Hybrid Rebeca language to support modeling of cyber-physical systems. Hybrid Rebeca is an extension of actor-based language Rebeca. In this extension, physical actors are introduced as new computational entities to encapsulate physical behaviors. To support various means of communication among the entities, the network is explicitly modeled as a separate entity from actors. We derive hybrid automata as the basis for analysis of Hybrid Rebeca models. We demonstrate the applicability of our approach through a case study in the domain of automotive systems. We use SpaceEx framework for the analysis of the case study.

eess.SY

Modelling and Simulation of Asynchronous Real-Time Systems using Timed Rebeca

In this paper we propose an extension of the Rebeca language that can be used to model distributed and asynchronous systems with timing constraints. We provide the formal semantics of the language using Structural Operational Semantics, and show its expressiveness by means of examples. We developed a tool for automated translation from timed Rebeca to the Erlang language, which provides a first implementation of timed Rebeca. We can use the tool to set the parameters of timed Rebeca models, which represent the environment and component variables, and use McErlang to run multiple simulations for different settings. Timed Rebeca restricts the modeller to a pure asynchronous actor-based paradigm, where the structure of the model represents the service oriented architecture, while the computational model matches the network infrastructure. Simulation is shown to be an effective analysis support, specially where model checking faces almost immediate state explosion in an asynchronous setting.

cs.SE