Types from data: Making structured data first-class citizens in F#
Most modern applications interact with external services and access data in structured formats such as XML, JSON and CSV. Static type systems do not understand such formats, often making data access more cumbersome. Should we give up and leave the messy world of external data to dynamic typing and runtime checks? Of course, not!
In this paper, we integrate external structured data into F# programming. As most real-world data does not come with an explicit schema, we develop a shape inference algorithm that infers a shape from representative sample documents and transforms the shape into F# types using type providers. We present a formalization and a relative type soundness theorem for a simplified version of this process.
Our library significantly reduces the amount of data access code and it provides additional safety guarantees when contrasted with the widely used weakly typed techniques.
Thu 16 Jun Times are displayed in time zone: Tijuana, Baja California change
15:30 - 17:00: Types IIResearch Papers at Grand Ballroom San Rafael Chair(s): Jean YangCarnegie Mellon University | |||
15:30 - 16:00 Talk | Just-in-Time Static Type Checking for Dynamic Languages Research Papers Brianna M. RenUniversity of Maryland, College Park, Jeffrey S. FosterUniversity of Maryland, College Park Media Attached | ||
16:00 - 16:30 Talk | Types from data: Making structured data first-class citizens in F# Research Papers Tomas PetricekUniversity of Cambridge, UK, Don SymeMicrosoft, Gustavo GuerraMicrosoft Corporation, London Pre-print Media Attached | ||
16:30 - 17:00 Talk | Automatically Learning Shape Specifications Research Papers He ZhuPurdue University, Gustavo PetriLIAFA, Université Paris Diderot, Suresh JagannathanPurdue University Media Attached |