Testing versus proving in climate impact research
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| Titel: | Testing versus proving in climate impact research |
|---|---|
| Autoren: | Ionescu, Cezar, Jansson, Patrik, 1972 |
| Quelle: | Leibniz International Proceedings in Informatics, LIPIcs. 19:41-54 |
| Schlagwörter: | dependently-typed programming, formalization, climate impact research, domain-specific languages |
| Beschreibung: | Higher-order properties arise naturally in some areas of climate impact research. For example, "vulnerability measures", crucial in assessing the vulnerability to climate change of various regions and entities, must fulfill certain conditions which are best expressed by quantification over all increasing functions of an appropriate type. This kind of property is notoriously difficult to test. However, for the measures used in practice, it is quite easy to encode the property as a dependent type and prove it correct. Moreover, in scientific programming, one is often interested in correctness "up to implication": the program would work as expected, say, if one would use real numbers instead of floating-point values. Such counterfactuals are impossible to test, but again, they can be easily encoded as types and proven. We show examples of such situations (encoded in Agda), encountered in actual vulnerability assessments. |
| Dateibeschreibung: | electronic |
| Zugangs-URL: | https://research.chalmers.se/publication/167769 http://publications.lib.chalmers.se/records/fulltext/167769/local_167769.pdf |
| Datenbank: | SwePub |
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| Items | – Name: Title Label: Title Group: Ti Data: Testing versus proving in climate impact research – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ionescu%2C+Cezar%22">Ionescu, Cezar</searchLink><br /><searchLink fieldCode="AR" term="%22Jansson%2C+Patrik%22">Jansson, Patrik</searchLink>, 1972 – Name: TitleSource Label: Source Group: Src Data: <i>Leibniz International Proceedings in Informatics, LIPIcs</i>. 19:41-54 – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22dependently-typed+programming%22">dependently-typed programming</searchLink><br /><searchLink fieldCode="DE" term="%22formalization%22">formalization</searchLink><br /><searchLink fieldCode="DE" term="%22climate+impact+research%22">climate impact research</searchLink><br /><searchLink fieldCode="DE" term="%22domain-specific+languages%22">domain-specific languages</searchLink> – Name: Abstract Label: Description Group: Ab Data: Higher-order properties arise naturally in some areas of climate impact research. For example, "vulnerability measures", crucial in assessing the vulnerability to climate change of various regions and entities, must fulfill certain conditions which are best expressed by quantification over all increasing functions of an appropriate type. This kind of property is notoriously difficult to test. However, for the measures used in practice, it is quite easy to encode the property as a dependent type and prove it correct. Moreover, in scientific programming, one is often interested in correctness "up to implication": the program would work as expected, say, if one would use real numbers instead of floating-point values. Such counterfactuals are impossible to test, but again, they can be easily encoded as types and proven. We show examples of such situations (encoded in Agda), encountered in actual vulnerability assessments. – Name: Format Label: File Description Group: SrcInfo Data: electronic – Name: URL Label: Access URL Group: URL Data: <link linkTarget="URL" linkTerm="https://research.chalmers.se/publication/167769" linkWindow="_blank">https://research.chalmers.se/publication/167769</link><br /><link linkTarget="URL" linkTerm="http://publications.lib.chalmers.se/records/fulltext/167769/local_167769.pdf" linkWindow="_blank">http://publications.lib.chalmers.se/records/fulltext/167769/local_167769.pdf</link> |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.4230/LIPIcs.TYPES.2011.41 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 41 Subjects: – SubjectFull: dependently-typed programming Type: general – SubjectFull: formalization Type: general – SubjectFull: climate impact research Type: general – SubjectFull: domain-specific languages Type: general Titles: – TitleFull: Testing versus proving in climate impact research Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ionescu, Cezar – PersonEntity: Name: NameFull: Jansson, Patrik IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2013 Identifiers: – Type: isbn-print Value: 3939897493 – Type: isbn-print Value: 9783939897491 – Type: issn-print Value: 18688969 – Type: issn-locals Value: SWEPUB_FREE – Type: issn-locals Value: CTH_SWEPUB Numbering: – Type: volume Value: 19 Titles: – TitleFull: Leibniz International Proceedings in Informatics, LIPIcs Type: main |
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