About
Dr Ulrich Berger is a Reader in the Department of Computer Science, Swansea University.
Dr Ulrich Berger
Reader,
Computer Science
Telephone number
+44 (0) 1792 513380
Research Links
Office - 337
Third Floor
Computational Foundry
Bay Campus
Third Floor
Computational Foundry
Bay Campus
Available For Postgraduate Supervision
Publications
Research Highlights
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Berger, U. (2019). On the constructive and computational content of abstract mathematics. Mathesis Universalis, Computability and ProofSU Repository: https://cronfa.swan.ac.uk/Record/cronfa50301
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Berger, U., Matthes, R., & Setzer, A. (2019). Martin Hofmann’s case for non-strictly positive 1 data types. In 24th International Conference on Types for Proofs and Programs (pp. 1:1-1:22).
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Berger, U. & Petrovska, O. (n.d.) Optimized Program Extraction for Induction and Coinduction. In Sailing Routes in the World of Computation-80). Springer.
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Berger, U. (2016). Extracting nondeterministic concurrent programs. In Computer Science Logic 2016 (pp. 26:1-26:21).
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Berger, U. & HOU, T. (2016). A realizability interpretation of Church's simple theory of types. Mathematical Structures in Computer Science, 1-22.
All Research
Journal Articles
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Berger, U. & HOU, T. (2016). A realizability interpretation of Church's simple theory of types. Mathematical Structures in Computer Science, 1-22.
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Berger, U. & Spreen, D. (2016). A coinductive approach to computing with compact sets. Journal of Logic and Analysis, 8(3), 1-35.
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Berger, U., Seisenberger, M., & Woods, G. (2014). Extracting Imperative Programs from Proofs: In-place Quicksort. Leibniz International Proceedings in Informatics (LIPIcs), 26, 84-106.
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Berger, U. & Sion, L. (2009). A coinductive approach to verified exact real number computation. Electronic Communications of the EASST, 23, 15 pp.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa42
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Berger, U. & Kahle, R. (2011). From coinductive proofs to exact real arithmetic: theory and applications. Logical Methods in Computer Science, 7(1)
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Berger, U. (2008). A domain model characterising strong normalisation. Annals of Pure and Applied Logic, 156(1), 39-50.
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Berger, U. & Hou, T. (2008). Coinduction for Exact Real Number Computation. Theory of Computing Systems, 43(3-4), 394-408.
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Berger, U. & Escardó, M. (2005). Strong normalization for applied lambda calculi. Logical Methods in Computer Science, 1(2)
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Berger, U., Eberl, M., & Schwichtenberg, H. (2003). Term rewriting for normalization by evaluation. Information and Computation, 183(1), 19
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Berger, U. (2005). Uniform Heyting arithmetic. Annals of Pure and Applied Logic, 133(1-3), 125
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Berger, U. & Kahle, R. (2011). From coinductive proofs to exact real arithmetic: theory and applications. Logical Methods in Computer Science, 7(1)
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Berger, U., BLANCK, J., & KØBER, P. (2010). Domain representations of spaces of compact subsets. Mathematical Structures in Computer Science, 20(02), 107-126.
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Berger, U. (2008). Classical truth in higher types. MLQ, 54(3), 240-246.
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Berger, U. & Seisenberger, M. (2012). Proofs, Programs, Processes. Theory of Computing Systems, 51(3), 313-329.
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Berger, U. (2011). From coinductive proofs to exact real arithmetic: theory and applications. Logical Methods in Computer Science, 7(1), 8
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Berger, U. (2010). Realisability for Induction and Coinduction with Applications to Constructive Analysis. Journal of Universal Computer Science, 16(18), 2535-2555.
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Berger, U. & Hou, T. (2012). Typed vs. Untyped realizability. Electronic Notes in Theoretical Computer Science, 286, 57-71.
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Berger, U., Blanck, J., & KØBER, P. (2010). Domain representations of spaces of compact subsets. Mathematical Structures in Computer Science, 20(02), 107
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Abdul Rauf, R., Berger, U., & Setzer, A. (2008). A Provably Correct Translation of the λ-Calculus into a Mathematical Model of C++. Theory of Computing Systems, 43(3-4), 298-321.
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Berger, U., Lawrence, A., Forsberg, F., & Seisenberger, M. (2015). Extracting verified decision procedures: DPLL and Resolution. Logical Methods in Computer Science, 11(1)
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Berger, U., Jones, A., & Seisenberger, M. (2015). Program extraction applied to monadic parsing. Journal of Logic and Computation, exv078
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Berger, U., James, P., Lawrence, A., Roggenbach, M., & Seisenberger, M. (2018). Verification of the European Rail Traffic Management System in Real-Time Maude. Science of Computer Programming, 154, 61-88.
Authored Books
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Berger, U., Benton, D., Benton, D., Benton, D., Hall, K., & Rhys, R. (2009). Realisability and adequacy for (co)induction Schloss Dagstuhl - Leibniz-Zentrum für Informatik.
Book Chapters
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Berger, U. (2019). On the constructive and computational content of abstract mathematics. Mathesis Universalis, Computability and ProofSU Repository: https://cronfa.swan.ac.uk/Record/cronfa50301
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Berger, U., Miyamoto, K., Schwichtenberg, H., & Tsuiki, H. (2016). Logic for Gray-code computation. (pp. 69de Gruyter
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Berger, U. & Seisenberger, M. (2010). Proofs, Programs, Processes. Programs, Proofs, Processes (pp. 39-48). Springer
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Berger, U., Miyamoto, K., Schwichtenberg, H., & Seisenberger, M. (2011). Minlog - A Tool for Program Extraction Supporting Algebras and Coalgebras. Algebra and Coalgebra in Computer Science (pp. 393-399). Springer
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Berger, U. & Monika, S. (2010). Program extraction via typed realisability for induction and coinduction.. Series in Mathematical Logic. (pp. 157-181). Ontos VerlagSU Repository: https://cronfa.swan.ac.uk/Record/cronfa8008
Conference Contributions
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Berger, U., Matthes, R., & Setzer, A. (2019). Martin Hofmann’s case for non-strictly positive 1 data types. In 24th International Conference on Types for Proofs and Programs (pp. 1:1-1:22).
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Berger, U. & Petrovska, O. (n.d.) Optimized Program Extraction for Induction and Coinduction. In Sailing Routes in the World of Computation-80). Springer.
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Berger, U. (2016). Extracting nondeterministic concurrent programs. In Computer Science Logic 2016 (pp. 26:1-26:21).
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Berger, U. & Hou, T. (2014). Uniform Schemata for Proof Rules. In Computability in Europe 2015 (CiE 2015) (pp. 53-62). Springer.
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Berger, U. (2009). Proofs-as-programs in computable analysis. In Electronic Communications of the EASST (pp. 5 pp.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50
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Berger, U. & Berger, U. (2004). A computational interpretation of open induction. (pp. 326-334).
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Berger, U. (2009). From Coinductive Proofs to Exact Real Arithmetic. In Computer Science Logic, Lecture Notes in Computer Science (pp. 132Springer.
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Berger, U. & Setzer, A. (2018). Undecidability of Equality for Codata Types. In Coalgebraic Methods in Computer Science (pp. 34-55). Springer International Publishing.
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Berger, U., Matthes, R., & Setzer, A. (2019). Martin Hofmann’s case for non-strictly positive data types. In Leibniz International Proceedings in Informatics, LIPIcs
Supervision
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Enhanced realizability interpretation for extracting correct programs. (current)
PhDOther supervisor: Dr Monika Seisenberger -
'''Application of Proof-theoretic Methods to Natural Language Processing''' (awarded 2018)
PhDOther supervisor: Dr Anton SetzerOther supervisor: Dr Monika Seisenberger -
'Integration of the Process Algebra CSP in Dependent Type Theory - Formalisation and Verification.' (awarded 2018)
PhDOther supervisor: Dr Anton Setzer -
Implementing Prawf with Program Extraction and Case Studies for Sequent Calculus Rules (current)
MResOther supervisor: Dr Jens Blanck -
Deep Encoding: Where Genetic Algorithms and Numeral Systems Meet (current)
MResOther supervisor: Dr Arno Pauly
Taught Modules
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CS-205 Declarative Programming
This module provides an introduction to the functional and logic programming paradigms and gives students the opportunity to gain practical experience in using both.
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CS-M15 Directed studies in Logic and Computation
Students will be assigned specific study topics associated with their intended research topic. They will be expected to undertake specialised individual study under the direction of their tutor. Both students and lecturers will give talks on project related topics. The student talks are assessed.
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CSC375 Logic for Computer Science
This module provides an introduction to logic and its applications to computer science, in particular to the formal specification and verification of computer programs.
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CSC385 Modelling and Verification Techniques
This module will give an overview of the landscape and the state of the art of current modelling and verification techniques. Students will gain hands-on experience in using a tool for modelling and verification.
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CSCM75 Logic in Computer Science
This module provides an in-depth introduction to logic and its applications to computer science, as a sound basis for the formal specification and verification of computer programs. Student will also learn how to use an interactive proof tool and carry out interactive proofs themselves.
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CSCM85 Modelling and Verification Techniques
This module will give an overview of the landscape and the state of the art of current modelling and verification techniques. One particular tool for software verification will be studied in depth. Students will gain hands-on experience in using that tool.
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CSGM05 Directed Studies in Logic and Computation
Students will be assigned specific study topics associated with their project topic. They will be expected to undertake specialised individual study under the direction of their tutor. Both students and lecturers will give talks on project related topics. The student talks are assessed.