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Principles of Provenance group

• People
• Positions
• Projects
• Publications

Provenance refers to information about the source, origin, derivation or authorship of data. It has deep connections to topics such as program slicing, causality, explanation, and information flow security. The Principles of Provenance group performs fundamental research on provenance as well as principled system development.

• Sándor Bartha (Data Science CDT student)
• Prof. James Cheney (fearless leader)
• Frank Emrich (PhD student)
• Dr. Vashti Galpin (Postdoc)
• Dr. Wilmer Ricciotti (Postdoc)

• Dr. Sidahmed Benabderrahmane (Postdoc, now at New York University)
• Dr. Ghita Berrada (Postdoc, now at LSE)
• Dr. Arthur Chan (PhD)
• Dr. Stefan Fehrenbach (PhD, now at Proda)
• Dr. Simon Fowler (Research Software Engineer, now at University of Glasgow)
• Dr. Weili Fu (PhD, now at University of Freiburg)
• Xavier Gombau (MSc, visiting from UPC, Barcelona)
• Dr. Rudi Horn (PhD, now at Oracle)
• Himan Mookherjee (MSc)
• Dr. Roly Perera (Postdoc, now at The Alan Turing Institute/University of Bristol)
• Dr. James McKinna (now at Heriot-Watt University)
• Dr. Jan Stolarek (Postdoc, now at BinarApps sp. z o.o.)

No positions are available at the moment.

• Programming foundations for trusted data science, UK National Physical Laboratory collaboration, (2019--2021)
• Probabilistic property-based testing, joint with Vaishak Belle, PhD studentship funded by Huawei
• Skye: A programming language bridging theory and practice for scientific data curation, funded by an ERC Consolidator Grant (2016-2021)

• A Diagnostics Approach to Advanced Persistent Threat Prevention (ADAPT), in collaboration with Galois, Inc., Xerox PARC, and Oregon State University, funded by DARPA's Transparent Computing research program
• Language-integrated provenance, funded by a Google Research Award
• Provenance for configuration language security (Microsoft Research), in collaboration with Paul Anderson (Edinburgh) and Dimitrios Vytiniotis (MSR)
• Language-based provenance security (AFOSR EOARD)
• A Theory of Least Change for Bidirectional Transformations (EPSRC, 2013-2017), in collaboration with Perdita Stevens and James McKinna (Edinburgh) and Jeremy Gibbons (Oxford)
• DIACHRON: Provenance and archiving for Linked Data (EU FP7, 2013-2016)
• W3C Provenance Interchange Working Group.
• The Database Wiki system (funded by Google Research Awards and University of Edinburgh support).

• Eris: Efficiently measuRing dIscord in multidimensional Sources, Alberto Abelló and James Cheney. Published online, VLDB Journal. (arXiv)
• Comprehending queries over finite maps, Wilmer Ricciotti, to appear, PPDP 2023
• Tracking and viewing modifications in digital calibration certificates, Vashti Galpin and Ian Smith and Jean-Laurent Hippolyte, Acta IMEKO 12(1), 2023.
• Language-Integrated Query for Temporal Data, Simon Fowler, Vashti Galpin and James Cheney, GPCE 2022 (arXiv)
• Nominal matching logic, James Cheney and Maribel Fernandez, PPDP 2022 (arXiv)
• Constraint-based type inference for FreezeML, Frank Emrich, Jan Stolarek, James Cheney and Sam Lindley. ICFP 2022. (arXiv)
• Strongly Normalizing Higher-Order Queries, Wilmer Ricciotti and James Cheney, Logical Methods in Computer Science 18(3:23), special issue for FSCD 2020. (arXiv)
• A Formalization of SQL with Nulls, Wilmer Ricciotti and James Cheney, in press, Journal of Automated Reasoning. (arXiv)
• One Down, 699 to go: or, synthesizing compositional desugarings, Sándor Bartha, James Cheney, and Vaishak Belle, OOPSLA 2021. (arXiv)
• Separating Sessions Smoothly, Simon Fowler, Wen Kokke, Ornela Dardha, Sam Lindley, and J. Garrett Morris, CONCUR 2021
• A Typed Slicing Compilation of the Polymorphic RPC Calculus, Kwanghoon Choi, James Cheney, Sam Lindley and Bob Reynders, PPDP 2021 (arXiv)
• Comprehending nulls, James Cheney and Wilmer Ricciotti, DBPL 2021 (arXiv)
• Data provenance, quality and curation in metrology, James Cheney, Adriane Chapman, Joy Davidson, and Alistair Forbes, AMCTM XII, to appear, (arXiv)
• Multiparty Session Types for Safe Runtime Adaptation in an Actor Language, Paul Harvey, Simon Fowler, Ornela Dardha, and Simon J. Gay, ECOOP 2021
• Provenance expressiveness benchmarking on non-deterministic executions, Arthur Chan,James Cheney, and Pramod Bhatotia, TaPP 2021
• Curating Covid-19 data in Links, Vashti Galpin, James Cheney, IPAW 2021 demo paper (arXiv)
• A Rule Mining-based Advanced Persistent Threats Detection System, Sidahmed Benabderrahmane, Ghita Berrada, James Cheney, Petko Valtchev, IJCAI 2021. (arXiv)
• Query Lifting: Language-integrated query for heterogeneous nested collections, Wilmer Ricciotti and James Cheney. ESOP 2021. (arXiv)
• Cross-tier web programming for curated databases: a case study, Simon Fowler, Simon Harding, Joanna Sharman, and James Cheney. IJDC 16(1), 2021. (arXiv).
• Integrity Checking and Abnormality Detection of Provenance Records , Sheung Chi Chan, Ashish Gehani, Hassaan Irshad, and James Cheney, TaPP 2020
• Cross-tier web programming for curated databases: a case study, Simon Fowler, Simon Harding, Joanna Sharman, and James Cheney. Pre-proceedings, IDCC 2020 (arXiv).
• A Polymorphic RPC Calculus, Kwanghoon Choi, James Cheney, Simon Fowler and Sam Lindley, Science of Computer Programming 197:102499, October 2020. Preliminary version presented at SBMF 2019. (arXiv)
• Model-View-Update-Communicate: Session Types meet the Elm Architecture, Simon Fowler. ECOOP 2020
• Strongly normalizing higher-order relational queries, Wilmer Ricciotti and James Cheney. FSCD 2020.
• FreezeML: Complete and easy type inference for first-class polymorphism, Frank Emrich, Sam Lindley, Jan Stolarek, James Cheney, and Jonathan Coates. PLDI 2020. (arXiv)
• Language-Integrated Updatable Views, Rudi Horn, Simon Fowler and James Cheney, post-proceedings of IFL 2019. (arXiv)
• A Modular, Practical Test for a Programming Course, Jan Stolarek and Przemyslaw Nowak. SIGCSE 2020, p. 887-893
• A baseline for unsupervised advanced persistent threat detection in system-level provenance, Ghita Berrada, Sidahmed Benabderrahmane, James Cheney, William Maxwell, Himan Mookherjee, Alec Theriault, and Ryan Wright, Future Generation Computing Systems Volume 108, July 2020, Pages 401-413. (arXiv)
• Flexible graph matching and graph edit distance using answer set programming, Sheung Chi Chan and James Cheney, PADL 2020 (arXiv).
• ProvMark: A provenance expressiveness benchmarking system, Sheung Chi Chan, James Cheney, Pramod Bhatotia, Thomas Pasquier, Ashish Gehani, Hassaan Irshad, Lucian Carata and Margo Seltzer. Middleware 2019. (arXiv)
• Towards meta-interpretive learning of programming language semantics , Sándor Bartha and James Cheney, ILP 2019. (arXiv)
• Verified self-explaining computation, Jan Stolarek and James Cheney, MPC 2019. (arXiv)
• Mixing set and bag semantics, Wilmer Ricciotti and James Cheney, DBPL 2019 (arXiv)
• Language-integrated provenance by trace analysis, Stefan Fehrenbach and James Cheney, DBPL 2019 (arXiv)
• Provenance meets bidirectional transformations, Anthony Anjorin and James Cheney, TaPP 2019
• Aggregating unsupervised provenance anomaly detectors, Ghita Berrada and James Cheney, TaPP 2019
• TryLinks: An interactive tutorial system for a cross-tier Web programming language, Junao Wu, Arek Mikolajczak, and James Cheney, ProWeb 2019 (arXiv)
• Proof-relevant π-calculus: a constructive account of concurrency and causality, Roly Perera and James Cheney, Mathematical Structures in Computer Science 28(9):1541-1577, 2018.
• Abstracting Extensible Data Types; Or, Rows By Any Other Name, J. Garrett Morris and James McKinna, POPL 2019
• Explicit Auditing, Wilmer Ricciotti and James Cheney, ICTAC 2018 (arXiv)
• Incremental relational lenses, Rudi Horn, Roly Perera and James Cheney, ICFP 2018 (arXiv)
• Language-integrated provenance in Haskell, Jan Stolarek and James Cheney. The Art, Science and Engineering of Programming, 2(3):11, 2018.
• Language-integrated provenance, Stefan Fehrenbach and James Cheney, Science of Computer Programming 155:103--145, 2018. Special issue on PPDP 2016. (arXiv)
• A core calculus for provenance inspection, Wilmer Ricciotti, PPDP 2017: 187-198
• Strongly normalizing audited computation, Wilmer Ricciotti and James Cheney, CSL 2017, p. 36:1-36:21. (arXiv)
• Expressiveness benchmarking for system-level provenance, Sheung Chi Chan, James Cheney, Ashish Gehani, Ripduman Sohan, and Hassaan Irshad. TaPP 2017.
• Imperative Functional Programs that Explain their Work, Wilmer Ricciotti, Jan Stolarek, Roly Perera and James Cheney. ICFP 2017. (arXiv)
• μPuppet: A declarative subset of the Puppet configuration language, Weili Fu, Roly Perera, Paul Anderson and James Cheney, ECOOP 2017, p. 12:1--12:27. (arXiv)
• Language-integrated provenance, Stefan Fehrenbach and James Cheney, PPDP 2016, p. 214-227. (arXiv)
• Causally consistent dynamic slicing, Roly Perera, Deepak Garg and James Cheney, CONCUR 2016, p. 18:1-18:15.
• Provenance segmentation, Rui Abreu, Dave Archer, Erin Chapman, Hoda Eldardiry, James Cheney, and Adria Gascon, TaPP 2016.
• The Rationale of PROV, Luc Moreau, Paul Groth, James Cheney, Simon Miles and Timothy Lebo, Journal of Web Semantics, 35:235-257, 2015.
• Proof-relevant π-calculus, Roly Perera and James Cheney, LFMTP 2015, p. 46-70.
• Language-integrated provenance in Links, Stefan Fehrenbach and James Cheney, TaPP 2015.
• Dynamic provenance for SPARQL Updates, Harry Halpin and James Cheney, ISWC 2014, p. 425-440 (arxiv)
• Database Queries that Explain their Work, James Cheney, Amal Ahmed and Umut Acar. PPDP 2014, p. 271-282 (arXiv)

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