Elastic sheet-defined functions: Generalising spreadsheet functions to variable-size input arrays

Sheet-defined functions (SDFs) bring modularity and abstraction to the world of spreadsheets. Alas, end users naturally write SDFs that work over fixed-size arrays, which limits their reusability. To help end user programmers write more reusable SDFs, we describe a principled approach to generalisin...

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Bibliographic Details
Published inJournal of functional programming Vol. 30
Main Authors MCCUTCHEN, MATT, BORGHOUTS, JUDITH, GORDON, ANDREW D., PEYTON JONES, SIMON, SARKAR, ADVAIT
Format Journal Article
LanguageEnglish
Published Cambridge, UK Cambridge University Press 2020
Subjects
Algorithms
Arrays
Elastic sheets
End users
Modularity
Semantics
Spreadsheets
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Summary:Sheet-defined functions (SDFs) bring modularity and abstraction to the world of spreadsheets. Alas, end users naturally write SDFs that work over fixed-size arrays, which limits their reusability. To help end user programmers write more reusable SDFs, we describe a principled approach to generalising such functions to become elastic SDFs that work over inputs of arbitrary size. We prove that under natural, checkable conditions, our algorithm returns the principal generalisation of an input SDF. We describe a formal semantics and several efficient implementation strategies for elastic SDFs. A user study with spreadsheet users compares the human experience of programming with elastic SDFs to the alternative of relying on array-processing combinators. Our user study finds that the cognitive load of elastic SDFs is lower than for SDFs with map/reduce array combinators, the closest alternative solution.
ISSN:0956-7968
1469-7653
DOI:10.1017/S0956796820000234