Complex models in modern science and are now routinely expressed as software. The PLAS4Sci lab (Programming Languages and Systems for Science) at the School of Computing, University of Kent is a sub-group of the PLAS group focussed on improving the state-of-the-art in programming languages, programming systems, and programming tools to support the daily work of scientists.

People

• Dominic Orchard - Lab lead
• Laura Bocchi - Reader in Programming Languages
• Chinmayi Baramashetru - Postdocatoral Research Associate

Former members

• Benjamin Orchard - Research Assistant and Research Software Engineer
• Danielle Marshall - Research Assistant

External members

• Roly Perera - Senior Research Associate at ICCS in Cambridge
• Jay Torry - Dominic’s PhD student in Cambridge

Partners

 

Projects

• CamFort, a tool for verification and static analysis of Fortran, with a particular focus on verification techniques for numerical computation.

• fortran-src, a static-analysis framework for Fortran, written in Haskell.

News

• 10 March 2025 - New group member: Chinmayi Baramashetru
• 2 January 2025 - Artifact Evaluation at Climate Informatics 2024
• 11 November 2024 - An autumn of my talks on programming languages and software engineering for climate modelling
• 10 September 2024 - Summer School 2024 training: Typing for Python, Abstract mathematics for Climate Modelling, and some Julia
• 10 July 2024 - Hiring: 33-month postdoc position opportunity on Programming Languages and Systems for Climate Science
• 22 January 2024 - Dominic co-chairs the 1st ACM Workshop on Programming for the Planet in London
• 29 October 2023 - Training at AIMS Kigali and attending WCRP OSC 2023
• 4 May 2023 - Presentations at EGU23
• 21 April 2023 - Presentation and extended abstract at Climate Informatics 2023
• 12 October 2022 - Hello world

Publications

pdf, bib	Structuring Arrays with Algebraic Shapes, Jakub Bachurski, Alan Mycroft, Dominic Orchard. ARRAY@PLDI 2025: 1-16
pdf, bib	Cognacy Queries over Dependence Graphs for Transparent Visualisations, Joseph Bond, Cristina David, Minh Nguyen, Dominic Orchard, Roly Perera. ESOP (1) 2025: 144-171
pdf, bib	FTorch: a library for coupling PyTorch models to Fortran, Jack Atkinson, Athena Elafrou, Elliott Kasoar, Joseph G. Wallwork, Thomas Meltzer, Simon Clifford, Dominic Orchard, Chris Edsall. J. Open Source Softw. 10(109): 7602 (2025)
pdf, bib	fortran-src: Fortran static analysis infrastructure, Mistral Contrastin, Raoul Hidalgo Charman, Matthew Danish, Benjamin Orchard, Dominic Orchard, Andrew Rice, Jason Xu. J. Open Source Softw. 10(106): 7571 (2025)
pdf, bib	FTorch - lowering the technical barrier of incorporating ML into Fortran models, Dominic Orchard, Elliott Kasoar, Jack Atkinson, Thomas Meltzer, Simon Clifford, and Athena Elafrou. Presentation at (EGU 2024)
pdf, bib	Tools and techniques for modular, portable (Machine Learning) parameterisations, Jack Atkinson, Dominic Orchard, Elliott Kasoar, and Thomas Meltzer. Presentation at (EGU 2024)
pdf, bib	Programming Languages for the Future of Design Computation, Robert Aish, Al Fisher, Dominic Orchard, Jay Torry. Onward! 2024: 241-265
pdf, bib	Incremental units-of-measure verification, Matthew Danish, Dominic Orchard, Andrew Rice. CoRR abs/2406.02174 (2024)
pdf, bib	Reducing the overhead of coupled ML models between Python and Fortran: an application to Gravity Wave Parameterizations, Jack Atkinson, Simon Clifford, David Connelly, Chris Edsall, Athena Elafrou, Ed Gerber, Laura Mansfield, Dominic Orchard, Aditi Sheshadri, Y. Qiang Sun, Minah Yang Extended abstract at (Climate Informatics 2023)
pdf, bib	Fostering collaboration through improved software development practices for the ONEFlux eddy covariance data processing pipeline, Gilberto Pastorello, Carlo Trotta, Alessio Ribeca, Keith Beattie, Sy-Toan Ngo, Housen Chu, You-Wei Cheah, Danielle Christianson, Giacomo Nicolini, Sigrid Dengel, Diego Polidori, Peter Isaac, Matthew Archer, Dominic Orchard, Deb Agarwal, Sebastien Biraud, Margaret Torn, Dario Papale. Presentation at (EGU 2023)
pdf, bib	Guiding user annotations for units-of-measure verification, Dominic Orchard, Mistral Contrastin, Matthew Danish, Andrew Rice, Workshop on Human Aspects of Types and Reasoning Assistants (HATRA 2020)
pdf, bib	Learning units-of-measure from scientific code, Matthew Danish, Miltiadis Allamanis, Marc Brockschmidt, Andrew Rice, Dominic Orchard, Software Engineering for Science, 2019
pdf, bib	Monitoring networks through multiparty session types, Laura Bocchi, Tzu-Chun Chen, Romain Demangeon, Kohei Honda, Nobuko Yoshida, Theoretical Computer Science 669 (2017): 33-58
pdf	Scrap Your Reprinter: A Datatype Generic Algorithm for Layout-Preserving Refactoring, Harry Clarke, Dominic Orchard, IFL 2017
pdf, bib	Timed runtime monitoring for multiparty conversations, Rumyana Neykova, Laura Bocchi, Nobuko Yoshida, Formal Aspects Comput. 29(5): 877-910 (2017)
pdf, bib	Verifying Spatial Properties of Array Computations, Dominic Orchard, Mistral Contrastin, Matthew Danish, Andrew Rice, OOPSLA 2017
pdf, bib	Supporting software sustainability with lightweight specifications, Mistral Contrastin, Matthew Danish, Dominic Orchard, Andrew Rice, WSSSPE4 (2016)
pdf, bib	Units-of-Measure Correctness in Fortran Programs, Mistral Contrastin, Andrew C. Rice, Matthew Danish, Dominic Orchard, Computing in Science and Engineering 18(1): 102-107 (2016)
pdf, bib	Evolving Fortran types with inferred units-of-measure, Dominic Orchard, Andrew C. Rice, Oleg Oshmyan, J. Comput. Science 9: 156-162 (2015)
pdf, bib	A Computational Science Agenda for Programming Language Research, Dominic Orchard, Andrew C. Rice, ICCS 2014: 713-727
pdf, bib	Upgrading Fortran source code using automatic refactoring, Dominic Orchard, Andrew C. Rice, WRT@SPLASH 2013: 29-32