Towards Industrially Applicable Formal Methods: Three Small Steps and One Giant Leap. - John A. McDermid; Andy Galloway; Simon Burton 001; John A. Clark; Ian Toyn; Nigel J. Tracey; Samuel H. Valentine (ICFEM, 1998)

Testing Safety-Related Software: a Practical Handbook, by S. Gardiner (Editor), Springer-Verlag, 1999 (Book Review). - Simon Burton 001 (Softw. Test. Verification Reliab., 1999)

A Family-Oriented Software Development Process for Engine Controllers. - Karen Allenby; Simon Burton 001; Darren Lee Buttle; John A. McDermid; John Murdoch; Alan Stephenson; Mike Bardill; Stuart Hutchesson (PROFES, 2001)

Automated generation of high-integrity test suites from graphical specifications. - Simon Burton 001 (2002)

Detecting and resolving semantic pathologies in UML sequence diagrams. - Paul Baker; Paul Bristow; Clive Jervis; David J. King; Robert Thomson 002; Bill Mitchell; Simon Burton 001 (ESEC/SIGSOFT FSE, 2005)

Automotive functional safety = safety + security. - Simon Burton 001; Jürgen Likkei; Priyamvadha Vembar; Marko Wolf (SECURIT, 2012)

Dependability Challenges in the Model-Driven Engineering of Automotive Systems. - Rakshith Amarnath; Peter Munk; Eike Thaden; Arne Nordmann; Simon Burton 001 (ISSRE Workshops, 2016)

Making the Case for Safety of Machine Learning in Highly Automated Driving. - Simon Burton 001; Lydia Gauerhof; Christian Heinzemann (SAFECOMP Workshops, 2017)

Semi-automatic safety analysis and optimization. - Peter Munk; Andreas Abele; Eike Thaden; Arne Nordmann; Rakshith Amarnath; Markus Schweizer; Simon Burton 001 (DAC, 2018)

Structuring Validation Targets of a Machine Learning Function Applied to Automated Driving. - Lydia Gauerhof; Peter Munk; Simon Burton 001 (SAFECOMP, 2018)

Challenges in Assuring Highly Complex, High Volume Safety-Critical Software. - John MacGregor; Simon Burton 001 (SAFECOMP Workshops, 2018)

Confidence Arguments for Evidence of Performance in Machine Learning for Highly Automated Driving Functions. - Simon Burton 001; Lydia Gauerhof; Bibhuti Bhusan Sethy; Ibrahim Habli; Richard Hawkins (SAFECOMP Workshops, 2019)

Mind the gaps: Assuring the safety of autonomous systems from an engineering, ethical, and legal perspective. - Simon Burton 001; Ibrahim Habli; Tom Lawton; John A. McDermid; Phillip Morgan; Zoë Porter (Artif. Intell., 2020)

Invited: Hardware/Software Co-Synthesis and Co-Optimization for Autonomous Systems. - Wanli Chang 001; Shuai Zhao 004; Simon Burton 001; Haitong Wang; Ting Chen 002; Nan Chen; Neil C. Audsley (DAC, 2021)

Dynamic Risk Management for Safely Automating Connected Driving Maneuvers. - Marta Grobelna; João-Vitor Zacchi; Philipp Schleiß; Simon Burton 001 (EDCC, 2021)

Safety Assurance of Machine Learning for Chassis Control Functions. - Simon Burton 001; Iwo Kurzidem; Adrian Schwaiger; Philipp Schleiss; Michael Unterreiner; Torben Gräber; Philipp Becker (SAFECOMP, 2021)

Safety, Complexity, and Automated Driving: Holistic Perspectives on Safety Assurance. - Simon Burton 001; John A. McDermid; Philip Garnett; Rob Weaver (Computer, 2021)

Safety Assessment: From Black-Box to White-Box. - Iwo Kurzidem; Adam Misik; Philipp Schleiss; Simon Burton 001 (ISSRE Workshops, 2022)

Automating Safety Argument Change Impact Analysis for Machine Learning Components. - Carmen Cârlan; Lydia Gauerhof; Barbara Gallina; Simon Burton 001 (PRDC, 2022)

Logically Sound Arguments for the Effectiveness of ML Safety Measures. - Chih-Hong Cheng; Tobias Schuster; Simon Burton 001 (SAFECOMP Workshops, 2022)

Formally Compensating Performance Limitations for Imprecise 2D Object Detection. - Tobias Schuster; Emmanouil Seferis; Simon Burton 001; Chih-Hong Cheng (SAFECOMP, 2022)

A causal model of safety assurance for machine learning. - Simon Burton 001 (CoRR, 2022)

Safe AI - How is this Possible? - Harald Rueß; Simon Burton 001 (CoRR, 2022)

Unaligned but Safe - Formally Compensating Performance Limitations for Imprecise 2D Object Detection. - Tobias Schuster; Emmanouil Seferis; Simon Burton 001; Chih-Hong Cheng (CoRR, 2022)

Facilitating Change Implementation for Continuous ML-Safety Assurance. - Chih-Hong Cheng; Nguyen Anh Vu Doan; Balahari Balu; Franziska Schwaiger; Emmanouil Seferis; Simon Burton 001; Yassine Qamsane; Ankit Shukla 004; Yinchong Yang; Zhiliang Wu; Andreas Hapfelmeier; Ingo Thon (CoRR, 2022)

Safety Assurance with Ensemble-based Uncertainty Estimation and overlapping alternative Predictions in Reinforcement Learning. - Dirk Eilers; Simon Burton 001; Felippe Schmoeller da Roza; Karsten Roscher (SafeAI@AAAI, 2023)

AI for Safety: How to use Explainable Machine Learning Approaches for Safety Analyses. - Iwo Kurzidem; Simon Burton 001; Philipp Schleiss (AISafety/SafeRL@IJCAI, 2023)

Statistical Property Testing for Generative Models. - Emmanouil Seferis; Simon Burton 001; Chih-Hong Cheng (Tiny Papers @ ICLR, 2023)

Can Conformal Prediction Obtain Meaningful Safety Guarantees for ML Models? - Emmanouil Seferis; Simon Burton 001; Chih-Hong Cheng (Tiny Papers @ ICLR, 2023)

SafeSens - Uncertainty Quantification of Complex Perception Systems. - Iwo Kurzidem; Simon Burton 001; Philipp Schleiss (ITSC, 2023)

Safeguarding Learning-based Control for Smart Energy Systems with Sampling Specifications. - Chih-Hong Cheng; Venkatesh Prasad Venkataramanan; Pragya Kirti Gupta; Yun-Fei Hsu; Simon Burton 001 (PRDC, 2023)

Addressing uncertainty in the safety assurance of machine-learning. - Simon Burton 001; Benjamin Herd (Frontiers Comput. Sci., 2023)

Emergence in Multi-agent Systems: A Safety Perspective. - Philipp Altmann; Julian Schönberger; Steffen Illium; Maximilian Zorn; Fabian Ritz; Tom Haider; Simon Burton 001; Thomas Gabor (ISoLA (2), 2024)

Can you trust your Agent? The Effect of Out-of-Distribution Detection on the Safety of Reinforcement Learning Systems. - Tom Haider; Karsten Roscher; Benjamin Herd; Felippe Schmoeller Roza; Simon Burton 001 (SAC, 2024)

Can you trust your ML metrics? Using Subjective Logic to determine the true contribution of ML metrics for safety. - Benjamin Herd; Simon Burton 001 (SAC, 2024)

Uncertainty-Aware Evaluation of Quantitative ML Safety Requirements. - Simon Burton 001; Benjamin Herd; João-Vitor Zacchi (SAFECOMP (Workshops), 2024)

A Deductive Approach to Safety Assurance: Formalising Safety Contracts with Subjective Logic. - Benjamin Herd; João-Vitor Zacchi; Simon Burton 001 (SAFECOMP (Workshops), 2024)

Safety Analysis of Autonomous Railway Systems: An Introduction to the SACRED Methodology. - Josh Hunter; John A. McDermid; Simon Burton 001 (CoRR, 2024)

Resilience and Antifragility of Autonomous Systems (Dagstuhl Seminar 24182). - Simon Burton 001; Radu Calinescu; Raffaela Mirandola (Dagstuhl Reports, 2024)

Insights from Railway Professionals: Rethinking Railway Assumptions Regarding Safety and Autonomy. - Josh Hunter; John A. McDermid; Simon Burton 001 (EDCC, 2025)

Assuring the Safety of Reinforcement Learning Components: AMLAS-RL. - Calum C. Imrie; Ioannis Stefanakos; Sepeedeh Shahbeigi; Richard Hawkins; Simon Burton 001 (CoRR, 2025)