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Marie Farrell

Publications and source records attributed to Marie Farrell.

At least 19 recordsLinked to original sources
arXiv2026

A Taxonomy of Human-Robot Teamwork Requirements

Autonomous systems are increasingly deployed in safety- and mission-critical domains where humans and robots must operate as a team to complete complex tasks. Existing requirements for Human-Robot teamwork remain fragmented across disparate sources, with no unified framework that addresses complexities of collaborative Human-Robot tasks. We address this gap by presenting a taxonomy of Human-Robot Teamwork (HRT) requirements derived from analysis of (academic and industrial) literature, standards and regulatory guidance. We extracted a construction corpus of 361 requirements from 14 cross-domain sources. Through iterative classification and refinement, we develop a two-level hierarchical taxonomy comprising 6 high-level categories and 21 low-level subcategories that distinguish information provision, relational control, decision support, safety mechanisms, performance monitoring, and foundational system capabilities. We validate the taxonomy through expert evaluation with 5 domain specialists and a utility demonstration on an independently assembled corpus of 448 requirements drawn from 19 sources spanning six HRT domains.

cs.SE↗
arXiv2026

Engineering Reliable Autonomous Systems: Challenges and Solutions

Engineering reliable autonomous systems is an important and growing topic in computer science. As autonomous systems become more prevalent, easy-to-use techniques for building them reliably are increasingly important. This workshop report captures and expands on the discussions at the Lorentz Center Workshop "Engineering Reliable Autonomous Systems" (ERAS), held from 10 to 14 June 2024. The workshop was co-organised by the organisers of the Workshop on Formal Methods for Autonomous Systems (FMAS) and the Workshop on Agents and Robots for reliable Engineered Autonomy (AREA). It brought together members of the FMAS and AREA communities, industry practitioners, and representatives from sectors where autonomous systems pose distinctive engineering challenges. The workshop focused on three main research topics: techniques for verification and validation of autonomous systems; engineering real-world autonomous systems; and software architectures for safe autonomous systems. Its main outcome is a catalogue of challenges in these areas and, most importantly, a pathway to solutions. Some challenges can already be tackled by techniques that are well known in academia but have not yet become regularly used in practice. Other challenges remain unresolved and require further research. This roadmap is intended to support future research and industrial collaboration.

cs.RO↗
arXiv2026

Towards Responsibly Non-Compliant Machines

We consider the problem of engineering autonomous intelligent agents that are capable to responsibly not comply with user requests. We argue that machine non-compliance comes in many different forms, and sketch the issues we should pursue on the road of accomplishing responsibly non-compliant intelligent machines. We anchor responsible non-compliance in justifications for task refusal, pathways to override the non-compliance, as well as careful tracking of security risks and liability transfers.

cs.AI↗
arXiv2026

An Abstract Architecture for Explainable Autonomy in Hazardous Environments

Autonomous robotic systems are being proposed for use in hazardous environments, often to reduce the risks to human workers. In the immediate future, it is likely that human workers will continue to use and direct these autonomous robots, much like other computerised tools but with more sophisticated decision-making. Therefore, one important area on which to focus engineering effort is ensuring that these users trust the system. Recent literature suggests that explainability is closely related to how trustworthy a system is. Like safety and security properties, explainability should be designed into a system, instead of being added afterwards. This paper presents an abstract architecture that supports an autonomous system explaining its behaviour (explainable autonomy), providing a design template for implementing explainable autonomous systems. We present a worked example of how our architecture could be applied in the civil nuclear industry, where both workers and regulators need to trust the system's decision-making capabilities.

cs.RO↗
arXiv2026

Counterexample-Guided Interval Weakening

Systems deployed for long periods of time in dynamic environments may experience performance degradation that affects timing guarantees, even when their functional behaviour remains unchanged. In the design and verification of critical systems, such timing guarantees are often expressed using Metric Temporal Logic (MTL). Under degradation, these specifications may no longer hold as stated, although weaker variants that relax timing bounds may still be satisfied and remain meaningful. For example, while an elevator may initially be required to arrive within 30 seconds of a request, degradation of its motor may only allow us to guarantee arrival within 60 seconds. Although weaker, this guarantee is still useful and allows the system to maintain a reasonable level of operation. In this paper we present CEGIW, an iterative, counterexample-guided algorithm for automatically weakening timing intervals in MTL specifications so that they hold for a given system model. The algorithm preserves the logical structure of the original specification and weakens only interval bounds. We prove the correctness and optimality of CEGIW, and conduct an empirical evaluation to demonstrate the practicality of interval weakening using formalised requirements from a number of real-world case-studies. Using a model checker to produce counterexamples, CEGIW either identifies the strongest interval weakening under which the specification holds, or determines that no such weakening exists.

cs.LO↗
arXiv2025

Automated Formalization of Probabilistic Requirements from Structured Natural Language

Integrating autonomous and adaptive behavior into software-intensive systems presents significant challenges for software development, as uncertainties in the environment or decision-making processes must be explicitly captured. These challenges are amplified in safety- and mission-critical systems, which must undergo rigorous scrutiny during design and development. Key among these challenges is the difficulty of specifying requirements that use probabilistic constructs to capture the uncertainty affecting these systems. To enable formal analysis, such requirements must be expressed in precise mathematical notations such as probabilistic logics. However, expecting developers to write requirements directly in complex formalisms is unrealistic and highly error-prone. We extend the structured natural language used by NASA's Formal Requirement Elicitation Tool (FRET) with support for the specification of unambiguous and correct probabilistic requirements, and develop an automated approach for translating these requirements into logical formulas. We propose and develop a formal, compositional, and automated approach for translating structured natural-language requirements into formulas in probabilistic temporal logic. To increase trust in our formalizations, we provide assurance that the generated formulas are well-formed and conform to the intended semantics through an automated validation framework and a formal proof. The extended FRET tool enables developers to specify probabilistic requirements in structured natural language, and to automatically translate them into probabilistic temporal logic, making the formal analysis of autonomous and adaptive systems more practical and less error-prone.

cs.PL↗
arXiv2025

Towards A Catalogue of Requirement Patterns for Space Robotic Missions

In the development of safety and mission-critical systems, including autonomous space robotic missions, complex behaviour is captured during the requirements elicitation phase. Requirements are typically expressed using natural language which is ambiguous and not amenable to formal verification methods that can provide robust guarantees of system behaviour. To support the definition of formal requirements, specification patterns provide reusable, logic-based templates. A suite of robotic specification patterns, along with their formalisation in NASA's Formal Requirements Elicitation Tool (FRET) already exists. These pre-existing requirement patterns are domain agnostic and, in this paper we explore their applicability for space missions. To achieve this we carried out a literature review of existing space missions and formalised their requirements using FRET, contributing a corpus of space mission requirements. We categorised these requirements using pre-existing specification patterns which demonstrated their applicability in space missions. However, not all of the requirements that we formalised corresponded to an existing pattern so we have contributed 5 new requirement specification patterns as well as several variants of the existing and new patterns. We also conducted an expert evaluation of the new patterns, highlighting their benefits and limitations.

cs.LO↗
arXiv2025

Safe-ROS: An Architecture for Autonomous Robots in Safety-Critical Domains

Deploying autonomous robots in safety-critical domains requires architectures that ensure operational effectiveness and safety compliance. In this paper, we contribute the Safe-ROS architecture for developing reliable and verifiable autonomous robots in such domains. It features two distinct subsystems: (1) an intelligent control system that is responsible for normal/routine operations, and (2) a Safety System consisting of Safety Instrumented Functions (SIFs) that provide formally verifiable independent oversight. We demonstrate Safe-ROS on an AgileX Scout Mini robot performing autonomous inspection in a nuclear environment. One safety requirement is selected and instantiated as a SIF. To support verification, we implement the SIF as a cognitive agent, programmed to stop the robot whenever it detects that it is too close to an obstacle. We verify that the agent meets the safety requirement and integrate it into the autonomous inspection. This integration is also verified, and the full deployment is validated in a Gazebo simulation, and lab testing. We evaluate this architecture in the context of the UK nuclear sector, where safety and regulation are crucial aspects of deployment. Success criteria include the development of a formal property from the safety requirement, implementation, and verification of the SIF, and the integration of the SIF into the operational robotic autonomous system. Our results demonstrate that the Safe-ROS architecture can provide safety verifiable oversight while deploying autonomous robots in safety-critical domains, offering a robust framework that can be extended to additional requirements and various applications.

cs.LO↗
arXiv2025

Revisiting Formal Methods for Autonomous Robots: A Structured Survey

This paper presents the initial results from our structured literature review on applications of Formal Methods (FM) to Robotic Autonomous Systems (RAS). We describe our structured survey methodology; including database selection and associated search strings, search filters and collaborative review of identified papers. We categorise and enumerate the FM approaches and formalisms that have been used for specification and verification of RAS. We investigate FM in the context of sub-symbolic AI-enabled RAS and examine the evolution of how FM is used over time in this field. This work complements a pre-existing survey in this area and we examine how this research area has matured over time. Specifically, our survey demonstrates that some trends have persisted as observed in a previous survey. Additionally, it recognized new trends that were not considered previously including a noticeable increase in adopting Formal Synthesis approaches as well as Probabilistic Verification Techniques.

cs.RO↗
arXiv2025

Supporting Software Formal Verification with Large Language Models: An Experimental Study

Formal methods have been employed for requirements verification for a long time. However, it is difficult to automatically derive properties from natural language requirements. SpecVerify addresses this challenge by integrating large language models (LLMs) with formal verification tools, providing a more flexible mechanism for expressing requirements. This framework combines Claude 3.5 Sonnet with the ESBMC verifier to form an automated workflow. Evaluated on nine cyber-physical systems from Lockheed Martin, SpecVerify achieves 46.5% verification accuracy, comparable to NASA's CoCoSim, but with lower false positives. Our framework formulates assertions that extend beyond the expressive power of LTL and identifies falsifiable cases that are missed by more traditional methods. Counterexample analysis reveals CoCoSim's limitations stemming from model connection errors and numerical approximation issues. While SpecVerify advances verification automation, our comparative study of Claude, ChatGPT, and Llama shows that high-quality requirements documentation and human monitoring remain critical, as models occasionally misinterpret specifications. Our results demonstrate that LLMs can significantly reduce the barriers to formal verification, while highlighting the continued importance of human-machine collaboration in achieving optimal results.

cs.SE↗
arXiv2025

Adventures in FRET and Specification

This paper gives an overview of previous work in which the authors used NASA's Formal Requirement Elicitation Tool (FRET) to formalise requirements. We discuss four case studies where we used FRET to capture the system's requirements. These formalised requirements subsequently guided the case study specifications in a combination of formal paradigms. For each case study we summarise insights gained during this process, exploring the expressiveness and the potential interoperability of these approaches. Our experience confirms FRET's suitability as a framework for the elicitation and understanding of requirements and for providing traceability from requirements to specification.

cs.SE↗
arXiv2023

Proceedings Fifth International Workshop on Formal Methods for Autonomous Systems

This EPTCS volume contains the proceedings for the Fifth International Workshop on Formal Methods for Autonomous Systems (FMAS 2023), which was held on the 15th and 16th of November 2023. FMAS 2023 was co-located with 18th International Conference on integrated Formal Methods (iFM) (iFM'22), organised by Leiden Institute of Advanced Computer Science of Leiden University. The workshop itself was held at Scheltema Leiden, a renovated 19th Century blanket factory alongside the canal. FMAS 2023 received 25 submissions. We received 11 regular papers, 3 experience reports, 6 research previews, and 5 vision papers. The researchers who submitted papers to FMAS 2023 were from institutions in: Australia, Canada, Colombia, France, Germany, Ireland, Italy, the Netherlands, Sweden, the United Kingdom, and the United States of America. Increasing our number of submissions for the third year in a row is an encouraging sign that FMAS has established itself as a reputable publication venue for research on the formal modelling and verification of autonomous systems. After each paper was reviewed by three members of our Programme Committee we accepted a total of 15 papers: 8 long papers and 7 short papers.

cs.AI↗
arXiv2022

Proceedings Fourth International Workshop on Formal Methods for Autonomous Systems (FMAS) and Fourth International Workshop on Automated and verifiable Software sYstem DEvelopment (ASYDE)

This EPTCS volume contains the joint proceedings for the fourth international workshop on Formal Methods for Autonomous Systems (FMAS 2022) and the fourth international workshop on Automated and verifiable Software sYstem DEvelopment (ASYDE 2022), which were held on the 26th and 27th of September 2022. FMAS 2022 and ASYDE 2022 were held in conjunction with 20th International Conference on Software Engineering and Formal Methods (SEFM'22), at Humboldt University in Berlin. For FMAS, this year's workshop was our return to having in-person attendance after two editions of FMAS that were entirely online because of the restrictions necessitated by COVID-19. We were also keen to ensure that FMAS 2022 remained easily accessible to people who were unable to travel, so the workshop facilitated remote presentation and attendance. The goal of FMAS is to bring together leading researchers who are using formal methods to tackle the unique challenges presented by autonomous systems, to share their recent and ongoing work. Autonomous systems are highly complex and present unique challenges for the application of formal methods. Autonomous systems act without human intervention, and are often embedded in a robotic system, so that they can interact with the real world. As such, they exhibit the properties of safety-critical, cyber-physical, hybrid, and real-time systems. We are interested in work that uses formal methods to specify, model, or verify autonomous and/or robotic systems; in whole or in part. We are also interested in successful industrial applications and potential directions for this emerging application of formal methods.

cs.LO↗
arXiv2022

A Compositional Approach to Verifying Modular Robotic Systems

Robotic systems used in safety-critical scenarios often rely on modular software architectures, and increasingly include autonomous components. Verifying that these modular robotic systems behave as expected requires approaches that can cope with, and preferably take advantage of, this inherent modularity. This paper describes a compositional approach to specifying the nodes in robotic systems built using the Robot Operating System (ROS), where each node is specified using First-Order Logic (FOL) Assume-Guarantee contracts that link the specification to the ROS implementation. We introduce inference rules that facilitate the composition of these node-level contracts to derive system-level properties. We also present a novel Domain-Specific Language, the ROS Contract Language (RCL), which captures a node's FOL specification and links this contract to its implementation. RCL contracts can be automatically translated, by our tool Vanda, into executable monitors; which we use to verify the contracts at runtime. We illustrate our approach through the specification and verification of an autonomous rover engaged in the remote inspection of a nuclear site, and finish with smaller examples that illustrate other useful features of our framework.

cs.LO↗
arXiv2022

Modelling the Turtle Python library in CSP

Software verification is an important tool in establishing the reliability of critical systems. One potential area of application is in the field of robotics, as robots take on more tasks in both day-to-day areas and highly specialised domains. Robots are usually given a plan to follow, if there are errors in this plan the robot will not perform reliably. The capability to check plans for errors in advance could prevent this. Python is a popular programming language in the robotics domain, through the use of the Robot Operating System (ROS) and various other libraries. Python's Turtle package provides a mobile agent, which we formally model here using Communicating Sequential Processes (CSP). Our interactive toolchain CSP2Turtle with CSP model and Python components, enables Turtle plans to be verified in CSP before being executed in Python. This means that certain classes of errors can be avoided, and provides a starting point for more detailed verification of Turtle programs and more complex robotic systems. We illustrate our approach with examples of robot navigation and obstacle avoidance in a 2D grid-world.

cs.RO↗
arXiv2022

Why just FRET when you can Refactor? Retuning FRETISH Requirements

Formal verification of a software system relies on formalising the requirements to which it should adhere, which can be challenging. While formalising requirements from natural-language, we have dependencies that lead to duplication of information across many requirements, meaning that a change to one requirement causes updates in several places. We propose to adapt code refactorings for NASA's Formal Requirements Elicitation Tool (FRET), our tool-of-choice. Refactoring is the process of reorganising software to improve its internal structure without altering its external behaviour; it can also be applied to requirements, to make them more manageable by reducing repetition. FRET automatically translates requirements (written in its input language Fretish) into Temporal Logic, which enables us to formally verify that refactoring has preserved the requirements' underlying meaning. In this paper, we present four refactorings for Fretish requirements and explain their utility. We describe the application of one of these refactorings to the requirements of a civilian aircraft engine software controller, to decouple the dependencies from the duplication, and analyse how this changes the number of requirements and the number of repetitions. We evaluate our approach using Spot, a tool for checking equivalence of Temporal Logic specifications.

cs.SE↗
arXiv2022

Towards Refactoring FRETish Requirements

Like software, requirements evolve and change frequently during the development process. Refactoring is the process of reorganising software without changing its behaviour, to make it easier to understand and modify. We propose refactoring for formalised requirements to reduce repetition in the requirement set so that they are easier to maintain as the system and requirements evolve. This work-in-progress paper describes our motivation for and initial approach to refactoring requirements in NASA's Formal Requirements Elicitation Tool (FRET). This work was directly triggered by our experience with an industrial aircraft engine software controller use case. In this paper, we reflect on the requirements that were obtained and, with a view to their maintainability, propose and outline functionality for refactoring FRETISH requirements.

cs.SE↗