Types from data: making structured data first-class citizens in F#
- Submitting institution
-
The University of Kent
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 10772
- Type
- E - Conference contribution
- DOI
-
10.1145/2908080.2908115
- Title of conference / published proceedings
- Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation - PLDI 2016
- First page
- 477
- Volume
- -
- Issue
- -
- ISSN
- 0362-1340
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2016
- URL
-
https://kar.kent.ac.uk/67140/
- Supplementary information
-
-
- 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
-
2
- Research group(s)
-
-
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is paper is significant because it describes the first practical method for extending a static type system with support for structured data, allowing programmers to safely access external data without the burden of explicit type annotations. We present a novel F# library underpinned by theoretical foundations providing a rigorous safety analysis. In addition to wide-spread industrial adoption with over 1.7M downloads; 96 open source academic and industrial contributors, including Compositional IT Ltd. The output has been given the PLDI Distinguished Paper award.
Web: https://github.com/fsprojects/FSharp.Data
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
