Datafun: A Functional Datalog
- Submitting institution
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University of Cambridge
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1916
- Type
- E - Conference contribution
- DOI
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10.1145/2951913.2951948
- Title of conference / published proceedings
- Proceedings of the 21st ACM SIGPLAN International Conference on Functional Programming
- First page
- 214
- Volume
- 51
- Issue
- 9
- ISSN
- 1523-2867
- Open access status
- Technical exception
- Month of publication
- September
- Year of publication
- 2016
- URL
-
-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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1
- Research group(s)
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-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper extended the Datalog first-order database query language to a full higher-order functional programming language. The design of Datalog has been surprisingly influential. Its design has had the expected dialogue with other query/analysis languages like Formulog and Flix, but somewhat unexpectedly, it has also had some influence on the design of languages aimed at supporting distributed programming with CRDTs (conflict-free replicated data types). The reason is that Datafun offers an easy-to-implement type system for checking the monotoncity of definitions, and monotonicity is one of the key properties needed to ensure the correctness of CRDT programs.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -