TY - JOUR
T1 - Ordered types for stream processing of tree-structured data
AU - Sato, Ryosuke
AU - Suenaga, Kohei
AU - Kobayashi, Naoki
N1 - Publisher Copyright:
© 2011 Information Processing Society of Japan.
Copyright:
Copyright 2015 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
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U2 - 10.2197/ipsjjip.19.74
DO - 10.2197/ipsjjip.19.74
M3 - Article
AN - SCOPUS:84941266112
VL - 19
SP - 74
EP - 87
JO - Journal of Information Processing
JF - Journal of Information Processing
SN - 0387-6101
ER -