Michael Durling

dblp:228/2483 · also Michael R. Durling · DBLP profile ↗
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6ranked-venue papers
0as first author
4since 2021 · last 2024
0000-0002-6660-2667ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 4 · 2 since 2021Security and privacy · 2 · 2 since 2021Theory of computation · 2 · 2 since 2021
YearPublicationVenuePosition
2024 Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificates
Udayan Mandal, Guy Amir, Haoze Wu 0001, Ieva Daukantas, Fletcher Lee Newell, Umberto J. Ravaioli, Baoluo Meng, Michael Durling, Milan Ganai, Tobey Shim, Guy Katz, Clark W. Barrett
FMCAD8
2024 Assurance Case Synthesis from a Curated Semantic Triplestore
Saswata Paul, Baoluo Meng, Kit Siu, Abha Moitra, Michael Durling
SAFECOMP5
2023 Towards a Correct-by-Construction Design of Integrated Modular Avionics
Baoluo Meng, Joyanta Debnath, Sarat Chandra Varanasi, Emmanuel Manoloios, Michael Durling, Saswata Paul, Daniel Prince, Saif Alsabbagh, Richard Haadsma, Craig McMillan, Tim Oates 0001
FMCAD5
2021 Automating the Assembly of Security Assurance Case Fragments
Baoluo Meng, Saswata Paul, Abha Moitra, Kit Siu, Michael Durling
SAFECOMP5
2019 Automating requirements analysis and test case generation
Abha Moitra, Kit Siu, Andrew W. Crapo, Michael Durling, Panagiotis Manolios, Michael Meiners, Craig McMillan
Requir. Eng.4
2018 Towards Development of Complete and Conflict-Free Requirements
abstract
Writing requirements is no easy task. Common problems include ambiguity in statements, specifications at the wrong level of abstraction, statements with inconsistent references to types, conflicting requirements, and incomplete requirements. These pitfalls lead to errors being introduced early in the design process. The longer the gap between error introduction and error discovery, the higher the cost associated with the error. To address the growing cost of system development, we introduce a tool called ASSERT" (Analysis of Semantic Specifications and Efficient generation of Requirements-based Tests) for capturing requirements, backed by a formal requirements analysis engine. ASSERT" also automatically generates a complete set of requirements-based test cases. Capturing requirements in an unambiguous way and then formally analyzing them with an automated theorem prover eliminates errors as soon as requirements are written. It also addresses the historical problem that analysis engines are hard to use for someone without formal methods expertise and analysis results are often difficult for the end-user to understand and make actionable. ASSERT"'s major contribution is to bring powerful requirements capture and analysis capability to the domain of the end-user. We provide explainable and automated formal analysis, something we found important for a tool's adoptability in industry.
Abha Moitra, Kit Siu, Andrew W. Crapo, Harsh Raju Chamarthi, Michael Durling, Panagiotis Manolios, Michael Meiners
RE5