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APLicative Programming with Naperian Functors by Jeremy Gibbons

Pexels Photo 1089438

We are still counting down the days until Lambda World! With so many amazing speakers to look forward to including the Closing Keynote with Jessica Rose, Technical Manager at FutureLearn we thought we would have another watch of last years amazing Closing Keynote given by Jeremy Gibbons on APLicative Programming with Naperian Functors. Check it out here. 




APLicative Programming with Naperian Functors

Much of the expressive power of array-oriented languages such as Iverson’s APL and J comes from their implicit lifting of scalar operations to act on higher-ranked data, for example to add a value to each element of a vector, or to add two compatible matrices pointwise. It is considered a shape error to attempt to combine arguments of incompatible shape, such as a 3-vector with a 4-vector. APL and J are dynamically typed, so such shape errors are caught only at run-time. Recent work by Slepak et al develops a custom type system for an array-oriented language, statically ruling out such errors. I will show that such a custom language design is unnecessary: the requisite compatibility checks can already be captured in modern expressive type systems, as found for example in Haskell; moreover, generative type-driven programming can exploit that static type information constructively to automatically induce the appropriate liftings. I will also show that the structure of multi-dimensional data is inherently a matter of traversable Naperian applicative functors (and I will explain what this means).


This talk was given by Jeremy Gibbons at Lambda World 2017.