Datalog may be considered either an unusually powerful query language or a
carefully limited logic programming language. Datalog is declarative,
expressive, and optimizable, and has been applied successfully in a wide
variety of problem domains. However, most use-cases require extending Datalog
in an application-specific manner. In this paper we define Datafun, an
analogue of Datalog supporting higher-order functional programming. The key
idea is to track monotonicity with types.
Tue 20 SepDisplayed time zone: Osaka, Sapporo, Tokyo change
Tue 20 Sep
Displayed time zone: Osaka, Sapporo, Tokyo change
10:35 - 12:15 | |||
10:35 25mTalk | A Glimpse of Hopjs Research Papers DOI | ||
11:00 25mTalk | Experience Report: Growing and Shrinking Polygons for Random Testing of Computational Geometry Algorithms Research Papers Ilya Sergey University College London, UK DOI | ||
11:25 25mTalk | Think Like a Vertex, Behave Like a Function! A Functional DSL for Vertex-Centric Big Graph Processing Research Papers Kento Emoto Kyushu Institute of Technology, Japan, Kiminori Matsuzaki Kochi University of Technology, Japan, Zhenjiang Hu National Institute of Informatics, Japan, Akimasa Morihata University of Tokyo, Japan, Hideya Iwasaki University of Electro-Communications, Japan DOI | ||
11:50 25mTalk | Datafun: A Functional Datalog Research Papers DOI | ||