Sun 23 Jun 2019 10:30 - 11:00 at 212B - Session I Chair(s): Neville Grech

"Datalog is declarative, optimizable, and relatively expressive. However, writing Datalog often involves repeating yourself; the restrictions that make Datalog practical also prevent ““higher-order”” idioms ─ for example, you cannot define a generic transitive closure operator. Datafun is a higher-order, typed functional language with Datalog-inspired semantics. In this talk, I’ll:

  1. Explain what Datafun is and how to write Datalog-style programs in Datafun.

  2. Give examples of Datafun’s increased expressivity.

  3. Show how Datafun’s support for semilattice aggregations is a natural fit for program analysis.

  4. Discuss why I think Datafun, although still in the design stage, has the potential to be implemented as efficiently as Datalog. In particular, we have recent work on generalizing seminaïve evaluation to Datafun."

Sun 23 Jun
Times are displayed in time zone: (GMT-07:00) Tijuana, Baja California change

09:30 - 11:00: DPA - Session I at 212B
Chair(s): Neville GrechUniversity of Athens
dpa-2019-papers09:30 - 10:00
Sandeep DasguptaUniversity of Illinois at Urbana-Champaign, USA
dpa-2019-papers10:00 - 10:30
Christoph ReichenbachLund University
dpa-2019-papers10:30 - 11:00
Michael ArntzeniusUniversity of Birmingham, UK