Related papers: Who is to Blame? Runtime Verification of Distribut…
Cyber-physical systems (CPS) designed in simulators, often consisting of multiple interacting agents (e.g. in multi-agent formations), behave differently in the real-world. We want to verify these systems during runtime when they are…
Networks are difficult to configure correctly, and tricky to debug. These problems are accentuated by temporal and stateful behavior. Static verification, while useful, is ineffectual for detecting behavioral deviations induced by hardware…
Runtime verification (RV) has the potential to enable the safe operation of safety-critical systems that are too complex to formally verify, such as Robot Operating System 2 (ROS2) applications. Writing correct monitors can itself be…
Runtime verification enables checking temporal logic specifications over individual execution traces and offers a scalable alternative to exhaustive formal verification. In practice, systems must satisfy dozens to hundreds of temporal…
We propose TOPL automata as a new method for runtime verification of systems with unbounded resource generation. Paradigmatic such systems are object-oriented programs which can dynamically generate an unbounded number of fresh object…
Remote run-time attestation methods, including Control Flow Attestation (CFA) and Data Flow Attestation (DFA), have been proposed to generate precise evidence of execution's control flow path (in CFA) and optionally execution data inputs…
Runtime Verification (RV) studies how to analyze execution traces of a system under observation. Stream Runtime Verification (SRV) applies stream transformations to obtain information from observed traces. Incomplete traces with information…
We present RVHyper, a runtime verification tool for hyperproperties. Hyperproperties, such as non-interference and observational determinism, relate multiple computation traces with each other. Specifications are given as formulas in the…
Verifying hyperproperties at runtime is a challenging problem as hyperproperties, such as non-interference and observational determinism, relate multiple computation traces with each other. It is necessary to store previously seen traces,…
Large language models can generate runnable software artifacts, but their security remains difficult to evaluate end to end. This study examines that problem through a Detect--Repair--Verify (DRV) workflow, in which vulnerabilities are…
Runtime Monitoring is a lightweight and dynamic verification technique that involves observing the internal operations of a software system and/or its interactions with other external entities, with the aim of determining whether the system…
This paper presents DMV-AVP, a distributed simulation of Multi-Vehicle Autonomous Valet Parking (AVP). The system was implemented as an application of the Distributed Multi-Autonomous Vehicle Architecture (DMAVA) for synchronized multi-host…
Behavior Trees (BTs) are high level controllers that have found use in a wide range of robotics tasks. As they grow in popularity and usage, it is crucial to ensure that the appropriate tools and methods are available for ensuring they work…
Interactions are formal models describing asynchronous communications within a Distributed System (DS). They can be drawn in the fashion of sequence diagrams and executed thanks to an operational semantics akin to that of process algebras.…
Runtime monitoring is an essential part of guaranteeing the safety of cyber-physical systems. Recently, runtime monitoring frameworks based on formal specification languages gained momentum. These languages provide valuable abstractions for…
In runtime verification, the central problem is to decide if a given program execution violates a given property. In online runtime verification, a monitor observes a program's execution as it happens. If the program being observed has hard…
In concurrent and distributed systems, software components are expected to communicate according to predetermined protocols and APIs - and if a component does not observe them, the system's reliability is compromised. Furthermore, isolating…
Reinforcement Learning with Verifiable Rewards (RLVR) has become a core training stage in recent large language models (LLMs). Its reliance on non-public, high-value prompt sets raises concerns about unauthorized data use, creating a need…
A Prolog-based framework for fully automated verification currently under development for heap-based object-oriented data is introduced. Dynamically allocated issues are discussed, recent approaches and criteria are analysed. The…
Vision-language-action (VLA) models trained on large-scale internet data and robot demonstrations have the potential to serve as generalist robot policies. However, despite their large-scale training, VLAs are often brittle to…