Ordered types for stream processing of tree-structured data

Ryosuke Sato, Kohei Suenaga, Naoki Kobayashi

Research output: Contribution to journalArticle

Abstract

Suenaga, et al. have developed a type-based framework for automatically translating tree-processing programs into stream-processing ones. The key ingredient of the framework was the use of ordered linear types to guarantee that a tree-processing program traverses an input tree just once in the depth-first, left-to-right order (so that the input tree can be read from a stream). Their translation, however, sometimes introduces redundant buffering of input data. This paper extends their framework by introducing ordered, non-linear types in addition to ordered linear types. The resulting transformation framework reduces the redundant buffering, generating more efficient stream-processing programs.

Original languageEnglish
Pages (from-to)74-87
Number of pages14
JournalJournal of information processing
Volume19
DOIs
Publication statusPublished - 2011
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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