Elastic Sheet-Defined Functions: Generalising Spreadsheet Functions to Variable-Size ...
summary
Automatic algorithm generalises sheet-defined functions to variable-size inputs by inferring length variables, emitting constraints and solving them like type inference to produce a principal regular generalization when it exists. Implementation labels cell references to avoid tile collisions and provides formal semantics plus several efficient strategies. Examples include SHOP, a bank interest ledger and a cascading-delay transit model. A user study using NASA TLX finds elastic SDFs lower cognitive load than array combinators and shows partial evidence of faster task completion.
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chapters (15)
- 0:00Intro
- 0:37A simple shopping spreadsheet
- 1:19Many shopping lists
- 1:50Sheet-defined function (SDF)
- 2:29A longer shopping list
- 3:05More complex: Compound interest
- 4:33Automatically resize the SDF
- 4:57Textual notation for SHOP
- 5:28Textual notation for elastic SHOP
- 5:46Calling an elastic SDF
- 6:22Best generalisation?
- 7:59Regular generalisations
- 8:32The generalisation algorithm
- 8:58Defining regularity: judgment calls • Need to exclude some well defined generalisations to have a principal regular generalisation
- 9:43User study findings: highlights
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