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597 строки
25 KiB
TeX
597 строки
25 KiB
TeX
\documentstyle[11pt,fullpage]{article}
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\begin{document}
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\def\AddSpace#1{\ifcat#1a\ \fi#1} % if next is a letter, add a space
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\def\YACC#1{{\sc Yacc}\AddSpace#1}
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\def\TWIG#1{{\sc Twig}\AddSpace#1}
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\def\PROG#1{{\sc Burg}\AddSpace#1}
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\def\PARSER#1{{\sc Burm}\AddSpace#1}
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\def\CODEGEN#1{{\sc Codegen}\AddSpace#1}
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\title{{\sc Burg} --- Fast Optimal Instruction Selection and Tree Parsing}
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\author{
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Christopher W. Fraser \\
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AT\&T Bell Laboratories \\
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600 Mountain Avenue 2C-464 \\
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Murray Hill, NJ 07974-0636 \\
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{\tt cwf@research.att.com}
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\and
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Robert R. Henry \\
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Tera Computer Company \\
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400 N. 34th St., Suite 300 \\
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Seattle, WA 98103-8600 \\
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{\tt rrh@tera.com}
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\and
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Todd A. Proebsting \\
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Dept. of Computer Sciences \\
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University of Wisconsin \\
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Madison, WI 53706 \\
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{\tt todd@cs.wisc.edu}
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}
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\date{December 1991}
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\maketitle
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\bibliographystyle{alpha}
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\newcommand\term[1]{{\it #1}}
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\newcommand\secref[1]{\S\ref{#1}}
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\newcommand\figref[1]{Figure~\ref{#1}}
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%
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% rationale table making
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%
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{\catcode`\^^M=13 \gdef\Obeycr{\catcode`\^^M=13 \def^^M{\\}}%
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\gdef\Restorecr{\catcode`\^^M=5 }} %
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%
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% for printing out options
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%
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\newcommand\option[1]{% #1=option character
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{\tt -#1}%
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}
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\newcommand\var[1]{%
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{\tt #1}%
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}
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\section{Overview}
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\PROG is a program that generates a fast tree parser using BURS
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(Bottom-Up Rewrite System) technology. It accepts a cost-augmented
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tree grammar and emits a C program that discovers in linear time an
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optimal parse of trees in the language described by the grammar. \PROG
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has been used to construct fast optimal instruction selectors for use
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in code generation. \PROG addresses many of the problems addressed by
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{\sc Twig}~\cite{aho-twig-toplas,appel-87}, but it is somewhat less flexible and
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much faster. \PROG is available via anonymous \var{ftp} from
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\var{kaese.cs.wisc.edu}. The compressed \var{shar} file
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\var{pub/burg.shar.Z} holds the complete distribution.
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This document describes only that fraction of the BURS model that is
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required to use \PROG. Readers interested in more detail might start
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with Reference~\cite{balachandran-complang}. Other relevant documents
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include References~\cite{kron-phd,hoffmann-jacm,hatcher-popl,chase-popl,pelegri-popl,pelegri-phd,wilhelm-tr,henry-budp,fraser-henry-spe-91,proebsting-91}.
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\section{Input}
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\PROG accepts a tree grammar and emits a BURS tree parser.
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\figref{fig-tree-grammar} shows a sample grammar that implements a very
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simple instruction selector.
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\begin{figure}
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\begin{verbatim}
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%{
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#define NODEPTR_TYPE treepointer
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#define OP_LABEL(p) ((p)->op)
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#define LEFT_CHILD(p) ((p)->left)
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#define RIGHT_CHILD(p) ((p)->right)
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#define STATE_LABEL(p) ((p)->state_label)
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#define PANIC printf
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%}
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%start reg
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%term Assign=1 Constant=2 Fetch=3 Four=4 Mul=5 Plus=6
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%%
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con: Constant = 1 (0);
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con: Four = 2 (0);
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addr: con = 3 (0);
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addr: Plus(con,reg) = 4 (0);
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addr: Plus(con,Mul(Four,reg)) = 5 (0);
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reg: Fetch(addr) = 6 (1);
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reg: Assign(addr,reg) = 7 (1);
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\end{verbatim}
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\caption{A Sample Tree Grammar\label{fig-tree-grammar}}
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\end{figure}
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\PROG grammars are structurally similar to \YACC's. Comments follow C
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conventions. Text between ``\var{\%\{}'' and ``\var{\%\}}'' is called
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the \term{configuration section}; there may be several such segments.
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All are concatenated and copied verbatim into the head of the generated
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parser, which is called \PARSER. Text after the second ``\var{\%\%}'',
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if any, is also copied verbatim into \PARSER, at the end.
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The configuration section configures \PARSER for the trees being parsed
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and the client's environment. This section must define
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\var{NODEPTR\_TYPE} to be a visible typedef symbol for a pointer to a
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node in the subject tree. \PARSER invokes \var{OP\_LABEL(p)},
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\var{LEFT\_CHILD(p)}, and \var{RIGHT\_CHILD(p)} to read the operator
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and children from the node pointed to by \var{p}. It invokes
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\var{PANIC} when it detects an error. If the configuration section
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defines these operations as macros, they are implemented in-line;
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otherwise, they must be implemented as functions. The section on
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diagnostics elaborates on \var{PANIC}.
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\PARSER computes and stores a single integral \term{state} in each node
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of the subject tree. The configuration section must define a macro
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\var{STATE\_LABEL(p)} to access the state field of the node pointed to
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by \var{p}. A macro is required because \PROG uses it as an lvalue. A
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C \var{short} is usually the right choice; typical code generation
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grammars require 100--1000 distinct state labels.
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The tree grammar follows the configuration section.
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\figref{fig-grammar-grammar} gives an EBNF grammar for \PROG tree
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grammars.
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\begin{figure}
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\begin{verbatim}
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grammar: {dcl} '%%' {rule}
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dcl: '%start' Nonterminal
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dcl: '%term' { Identifier '=' Integer }
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rule: Nonterminal ':' tree '=' Integer cost ';'
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cost: /* empty */
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cost: '(' Integer { ',' Integer } ')'
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tree: Term '(' tree ',' tree ')'
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tree: Term '(' tree ')'
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tree: Term
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tree: Nonterminal
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\end{verbatim}
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\caption{EBNF Grammar for Tree Grammars for \PROG\ \label{fig-grammar-grammar}}
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\end{figure}
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Comments, the text between ``\var{\%\{}'' and ``\var{\%\}}'', and the
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text after the optional second ``\var{\%\%}'' are treated lexically, so
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the figure omits them. In the EBNF grammar, quoted text must appear
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literally, \var{Nonterminal} and \var{Integer} are self-explanatory,
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and \var{Term} denotes an identifier previously declared as a
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terminal. {\tt\{$X$\}} denotes zero or more instances of $X$.
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Text before the first ``\var{\%\%}'' declares the start symbol and the
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terminals or operators in subject trees. All terminals must be
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declared; each line of such declarations begins with \var{\%term}.
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Each terminal has fixed arity, which \PROG infers from the rules using that terminal.
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\PROG restricts terminals to have at most two children. Each terminal
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is declared with a positive, unique, integral \term{external symbol
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number} after a ``\var{=}''. \var{OP\_LABEL(p)} must return the valid
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external symbol number for \var{p}. Ideally, external symbol numbers
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form a dense enumeration. Non-terminals are not declared, but the
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start symbol may be declared with a line that begins with
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\var{\%start}.
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Text after the first ``\var{\%\%}'' declares the rules. A tree grammar
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is like a context-free grammar: it has rules, non-terminals,
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terminals, and a special start non-terminal. The right-hand side of a
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rule, called the \term{pattern}, is a tree. Tree patterns appear in
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prefix parenthesized form. Every non-terminal denotes a tree. A chain
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rule is a rule whose pattern is another non-terminal. If no start
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symbol is declared, \PROG uses the non-terminal defined by the first
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rule. \PROG needs a single start symbol; grammars for which it is
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natural to use multiple start symbols must be augmented with an
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artificial start symbol that derives, with zero cost, the grammar's
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natural start symbols. \PARSER will automatically select one
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that costs least for any given tree.
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\PROG accepts no embedded semantic actions like \YACC's, because no one
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format suited all intended applications. Instead, each rule has a
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positive, unique, integral \term{external rule number}, after the
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pattern and preceded by a ``\var{=}''. Ideally, external rule numbers
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form a dense enumeration. \PARSER uses these numbers to report the
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matching rule to a user-supplied routine, which must implement any
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desired semantic action; see below. Humans may select these integers
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by hand, but \PROG is intended as a \term{server} for building BURS
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tree parsers. Thus some \PROG clients will consume a richer
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description and translate it into \PROG's simpler input.
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Rules end with a vector of non-negative, integer costs, in parentheses
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and separated by commas. If the cost vector is omitted, then all
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elements are assumed to be zero. \PROG retains only the first four
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elements of the list. The cost of a derivation is the sum of the costs
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for all rules applied in the derivation. Arithmetic on cost vectors
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treats each member of the vector independently. The tree parser finds
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the cheapest parse of the subject tree. It breaks ties arbitrarily.
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By default, \PROG uses only the \term{principal cost} of each cost
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vector, which defaults to the first element, but options described
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below provide alternatives.
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\section{Output}
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\PARSER traverses the subject tree twice. The first pass or
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\term{labeller} runs bottom-up and left-to-right, visiting each node
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exactly once. Each node is labeled with a state, a single number that
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encodes all full and partial optimal pattern matches viable at that
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node. The second pass or \term{reducer} traverses the subject tree
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top-down. The reducer accepts a tree node's state label and a
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\term{goal} non-terminal --- initially the root's state label and the
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start symbol --- which combine to determine the rule to be applied at
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that node. By construction, the rule has the given goal non-terminal
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as its left-hand side. The rule's pattern identifies the subject
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subtrees and goal non-terminals for all recursive visits. Here, a
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``subtree'' is not necessarily an immediate child of the current node.
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Patterns with interior operators cause the reducer to skip the
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corresponding subject nodes, so the reducer may proceed directly to
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grandchildren, great-grandchildren, and so on. On the other hand,
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chain rules cause the reducer to revisit the current subject node, with
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a new goal
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non-terminal, so \term{x} is also regarded as a subtree of \term{x}.
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As the reducer visits (and possibly revisits) each node, user-supplied
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code implements semantic action side effects and controls the order in
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which subtrees are visited. The labeller is self-contained, but the
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reducer combines code from \PROG with code from the user, so \PARSER
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does not stand alone.
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The \PARSER that is generated by \PROG provides primitives for
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labelling and reducing trees. These mechanisms are a compromise
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between expressibility, abstraction, simplicity, flexibility and
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efficiency. Clients may combine primitives into labellers and reducers
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that can traverse trees in arbitrary ways, and they may call semantic
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routines when and how they wish during traversal. Also, \PROG
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generates a few higher level routines that implement common
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combinations of primitives, and it generates mechanisms that help debug
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the tree parse.
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\PROG generates the labeller as a function named \var{burm\_label} with
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the signature
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\begin{verbatim}
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extern int burm_label(NODEPTR_TYPE p);
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\end{verbatim}
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It labels the entire subject tree pointed to by \var{p} and returns the
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root's state label. State zero labels unmatched trees. The trees may
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be corrupt or merely inconsistent with the grammar.
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The simpler \var{burm\_state} is \var{burm\_label} without the
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code to traverse the tree and to read and write its fields. It may be
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used to integrate labelling into user-supplied traversal code. A
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typical signature is
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\begin{verbatim}
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extern int burm_state(int op, int leftstate, int rightstate);
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\end{verbatim}
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It accepts an external symbol number for a node and the labels for the
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node's left and right children. It returns the state label to assign
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to that node. For unary operators, the last argument is ignored; for
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leaves, the last two arguments are ignored. In general, \PROG
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generates a \var{burm\_state} that accepts the maximum number of child
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states required by the input grammar. For example, if the grammar
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includes no binary operators, then \var{burm\_state} will have the
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signature
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\begin{verbatim}
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extern int burm_state(int op, int leftstate);
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\end{verbatim}
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This feature is included to permit future expansion to operators with
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more than two children.
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The user must write the reducer, but \PARSER writes code and data that
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help. Primary is
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\begin{verbatim}
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extern int burm_rule(int state, int goalnt);
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\end{verbatim}
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which accepts a tree's state label and a goal non-terminal and returns the
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external rule number of a rule. The rule will have matched the tree
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and have the goal non-terminal on the left-hand side; \var{burm\_rule}
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returns zero when the tree labelled with the given state did not match
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the goal non-terminal. For the initial, root-level call, \var{goalnt}
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must be one, and \PARSER exports an array that identifies the values
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for nested calls:
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\begin{verbatim}
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extern short *burm_nts[] = { ... };
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\end{verbatim}
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is an array indexed by external rule numbers. Each element points to a
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zero-terminated vector of short integers, which encode the goal
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non-terminals for that rule's pattern, left-to-right. The user needs
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only these two externals to write a complete reducer, but a third
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external simplifies some applications:
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\begin{verbatim}
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extern NODEPTR_TYPE *burm_kids(NODEPTR_TYPE p, int eruleno, NODEPTR_TYPE kids[]);
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\end{verbatim}
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accepts the address of a tree \var{p}, an external rule number, and an
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empty vector of pointers to trees. The procedure assumes that \var{p}
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matched the given rule, and it fills in the vector with the subtrees (in
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the sense described above) of \var{p} that must be reduced recursively.
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\var{kids} is returned. It is not zero-terminated.
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The simple user code below labels and then fully reduces a subject tree;
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the reducer prints the tree cover. \var{burm\_string} is defined below.
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\begin{verbatim}
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parse(NODEPTR_TYPE p) {
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burm_label(p); /* label the tree */
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reduce(p, 1, 0); /* and reduce it */
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}
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reduce(NODEPTR_TYPE p, int goalnt, int indent) {
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int eruleno = burm_rule(STATE_LABEL(p), goalnt); /* matching rule number */
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short *nts = burm_nts[eruleno]; /* subtree goal non-terminals */
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NODEPTR_TYPE kids[10]; /* subtree pointers */
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int i;
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for (i = 0; i < indent; i++)
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printf("."); /* print indented ... */
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printf("%s\n", burm_string[eruleno]); /* ... text of rule */
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burm_kids(p, eruleno, kids); /* initialize subtree pointers */
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for (i = 0; nts[i]; i++) /* traverse subtrees left-to-right */
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reduce(kids[i], nts[i], indent+1); /* and print them recursively */
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}
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\end{verbatim}
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The reducer may recursively traverse subtrees in any order, and it may
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interleave arbitrary semantic actions with recursive traversals.
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Multiple reducers may be written, to implement multi-pass algorithms
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or independent single-pass algorithms.
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For each non-terminal $x$, \PROG emits a preprocessor directive to
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equate \var{burm\_}$x$\var{\_NT} with $x$'s integral encoding. It also
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defines a macro \var{burm\_}$x$\var{\_rule(a)} that is equivalent to
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\var{burm\_rule(a,}$x$\var{)}. For the grammar in
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\figref{fig-tree-grammar}, \PROG emits
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\begin{verbatim}
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#define burm_reg_NT 1
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#define burm_con_NT 2
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#define burm_addr_NT 3
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#define burm_reg_rule(a) ...
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#define burm_con_rule(a) ...
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#define burm_addr_rule(a) ...
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\end{verbatim}
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Such symbols are visible only to the code after the second
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``\var{\%\%}''. If the symbols \var{burm\_}$x$\var{\_NT} are needed
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elsewhere, extract them from the \PARSER source.
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The \option{I} option directs \PROG to emit an encoding of the input
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that may help the user produce diagnostics. The vectors
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\begin{verbatim}
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extern char *burm_opname[];
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extern char burm_arity[];
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\end{verbatim}
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hold the name and number of children, respectively, for each terminal.
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They are indexed by the terminal's external symbol number. The vectors
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\begin{verbatim}
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extern char *burm_string[];
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extern short burm_cost[][4];
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\end{verbatim}
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hold the text and cost vector for each rule. They are indexed by the
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external rule number. The zero-terminated vector
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\begin{verbatim}
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extern char *burm_ntname[];
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\end{verbatim}
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is indexed by \var{burm\_}$x$\var{\_NT} and holds the name of
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non-terminal $x$. Finally, the procedures
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\begin{verbatim}
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extern int burm_op_label(NODEPTR_TYPE p);
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extern int burm_state_label(NODEPTR_TYPE p);
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extern NODEPTR_TYPE burm_child(NODEPTR_TYPE p, int index);
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\end{verbatim}
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are callable versions of the configuration macros.
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\var{burm\_child(p,0)} implements \var{LEFT\_CHILD(p)}, and
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\var{burm\_child(p,1)} implements \var{RIGHT\_CHILD(p)}. A sample use
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is the grammar-independent expression
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\var{burm\_opname[burm\_op\_label(p)]}, which yields the textual name
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for the operator in the tree node pointed to by \var{p}.
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A complete tree parser can be assembled from just \var{burm\_state},
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\var{burm\_rule}, and \var{burm\_nts}, which use none of the
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configuration section except \var{PANIC}. The generated routines that
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use the rest of the configuration section are compiled only if the
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configuration section defines \var{STATE\_LABEL}, so they can be
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omitted if the user prefers to hide the tree structure from \PARSER.
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This course may be wise if, say, the tree structure is defined in a
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large header file with symbols that might collide with \PARSER's.
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\PARSER selects an optimal parse without dynamic programming at compile
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time~\cite{aho-johnson-dp-classic}. Instead, \PROG does the dynamic
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programming at compile-compile time, as it builds \PARSER.
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Consequently, \PARSER parses quickly. Similar labellers have taken as
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few as 15 instructions per node, and reducers as few as 35 per node
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visited~\cite{fraser-henry-spe-91}.
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\section{Debugging}
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\PARSER invokes \var{PANIC} when an error prevents it from proceeding.
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\var{PANIC} has the same signature as \var{printf}. It should pass its
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arguments to \var{printf} if diagnostics are desired and then either
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abort (say via \var{exit}) or recover (say via \var{longjmp}). If it
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returns, \PARSER aborts. Some errors are not caught.
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\PROG assumes a robust preprocessor, so it omits full consistency
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checking and error recovery. \PROG constructs a set of states using a
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closure algorithm like that used in LR table construction. \PROG
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considers all possible trees generated by the tree grammar and
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summarizes infinite sets of trees with finite sets. The summary
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records the cost of those trees but actually manipulates the
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differences in costs between viable alternatives using a dynamic
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programming algorithm. Reference~\cite{henry-budp} elaborates.
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Some grammars derive trees whose optimal parses depend on arbitrarily
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distant data. When this happens, \PROG and the tree grammar
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\term{cost diverge}, and \PROG attempts to build an infinite
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set of states; it first thrashes and ultimately exhausts
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memory and exits. For example, the tree grammar in
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\figref{fig-diverge-grammar}
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\begin{figure}
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\begin{verbatim}
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%term Const=17 RedFetch=20 GreenFetch=21 Plus=22
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%%
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reg: GreenFetch(green_reg) = 10 (0);
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reg: RedFetch(red_reg) = 11 (0);
|
|
|
|
green_reg: Const = 20 (0);
|
|
green_reg: Plus(green_reg,green_reg) = 21 (1);
|
|
|
|
red_reg: Const = 30 (0);
|
|
red_reg: Plus(red_reg,red_reg) = 31 (2);
|
|
\end{verbatim}
|
|
\caption{A Diverging Tree Grammar\label{fig-diverge-grammar}}
|
|
\end{figure}
|
|
diverges, since non-terminals \var{green\_reg} and \var{red\_reg}
|
|
derive identical infinite trees with different costs. If the cost of
|
|
rule 31 is changed to 1, then the grammar does not diverge.
|
|
|
|
Practical tree grammars describing instruction selection do not
|
|
cost-diverge because infinite trees are derived from non-terminals
|
|
that model temporary registers. Machines can move data between
|
|
different types of registers for a small bounded cost, and the rules
|
|
for these instructions prevent divergence. For example, if
|
|
\figref{fig-diverge-grammar} included rules to move data between red
|
|
and green registers, the grammar would not diverge. If a bonafide
|
|
machine grammar appears to make \PROG loop, try a host with more
|
|
memory. To apply \PROG to problems other than instruction selection,
|
|
be prepared to consult the literature on
|
|
cost-divergence~\cite{pelegri-phd}.
|
|
|
|
\section{Running \PROG\ }\label{sec-man-page}
|
|
|
|
\PROG reads a tree grammar and writes a \PARSER in C. \PARSER can be
|
|
compiled by itself or included in another file. When suitably named
|
|
with the \option{p} option, disjoint instances of \PARSER should link
|
|
together without name conflicts. The command:
|
|
\begin{flushleft}
|
|
\var{burg} [ {\it arguments} ] [ {\it file} ]
|
|
\end{flushleft}
|
|
invokes \PROG. If a {\it file} is named, \PROG expects its grammar
|
|
there; otherwise it reads the standard input. The options include:
|
|
\def\Empty{}
|
|
%
|
|
\newcommand\odescr[2]{% #1=option character, #2=optional argument
|
|
\gdef\Arg2{#2}%
|
|
\item[\option{#1}\ifx\Arg2\Empty\else{{\it #2}}\fi]
|
|
}
|
|
\begin{description}
|
|
%
|
|
\odescr{c}{} $N$
|
|
Abort if any relative cost exceeds $N$, which keeps \PROG from looping on
|
|
diverging grammars. Several
|
|
references~\cite{pelegri-popl,henry-budp,balachandran-complang,proebsting-91}
|
|
explain relative costs.
|
|
%
|
|
\odescr{d}{}
|
|
Report a few statistics and flag unused rules and terminals.
|
|
%
|
|
\odescr{o}{} {\it file}
|
|
Write parser into {\it file}. Otherwise it writes to the standard output.
|
|
%
|
|
\odescr{p}{} {\it prefix}
|
|
Start exported names with {\it prefix}. The default is \var{burm}.
|
|
%
|
|
\odescr{t}{}
|
|
Generates smaller tables faster, but all goal non-terminals passed to
|
|
\var{burm\_rule} must come from an appropriate \var{burm\_nts}. Using
|
|
\var{burm\_}$x$\var{\_NT} instead may give unpredictable results.
|
|
%
|
|
\odescr{I}{}
|
|
Emit code for \var{burm\_arity}, \var{burm\_child}, \var{burm\_cost},
|
|
\var{burm\_ntname}, \var{burm\_op\_label}, \var{burm\_opname},
|
|
\var{burm\_state\_label}, and \var{burm\_string}.
|
|
%
|
|
\odescr{O}{} $N$
|
|
Change the principal cost to $N$. Elements of each cost vector are
|
|
numbered from zero.
|
|
%
|
|
\odescr{=}{}
|
|
Compare costs lexicographically, using all costs in the given order.
|
|
This option slows \PROG and may produce a larger parser. Increases
|
|
range from small to astronomical.
|
|
\end{description}
|
|
|
|
\section{Acknowledgements}
|
|
|
|
The first \PROG was adapted by the second author from his \CODEGEN
|
|
package, which was developed at the University of Washington with
|
|
partial support from NSF Grant CCR-88-01806. It was unbundled from
|
|
\CODEGEN with the support of Tera Computer. The current \PROG was
|
|
written by the third author with the support of NSF grant
|
|
CCR-8908355. The interface, documentation, and testing involved
|
|
all three authors.
|
|
|
|
Comments from a large group at the 1991 Dagstuhl Seminar on Code
|
|
Generation improved \PROG's interface. Robert Giegerich and Susan
|
|
Graham organized the workshop, and the International Conference and
|
|
Research Center for Computer Science, Schloss Dagstuhl, provided an
|
|
ideal environment for such collaboration. Beta-testers included Helmut
|
|
Emmelmann, Dave Hanson, John Hauser, Hugh Redelmeier, and Bill Waite.
|
|
|
|
\begin{thebibliography}{BMW87}
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\bibitem[AGT89]{aho-twig-toplas}
|
|
Alfred~V. Aho, Mahadevan Ganapathi, and Steven W.~K. Tjiang.
|
|
\newblock Code generation using tree matching and dynamic programming.
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|
\newblock {\em ACM Transactions on Programming Languages and Systems},
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11(4):491--516, October 1989.
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|
|
\bibitem[AJ76]{aho-johnson-dp-classic}
|
|
Alfred~V. Aho and Steven~C. Johnson.
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\newblock Optimal code generation for expression trees.
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|
\newblock {\em Journal of the ACM}, 23(3):458--501, July 1976.
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\bibitem[App87]{appel-87}
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Andrew~W. Appel.
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\newblock Concise specification of locally optimal code generators.
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\newblock Technical report CS-TR-080-87, Princeton University, 1987.
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\bibitem[BDB90]{balachandran-complang}
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A.~Balachandran, D.~M. Dhamdhere, and S.~Biswas.
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\newblock Efficient retargetable code generation using bottom-up tree pattern
|
|
matching.
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\newblock {\em Computer Languages}, 15(3):127--140, 1990.
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\bibitem[BMW87]{wilhelm-tr}
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J\"{u}rgen B\"{o}rstler, Ulrich M\"{o}nche, and Reinhard Wilhelm.
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\newblock Table compression for tree automata.
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\newblock Technical Report Aachener Informatik-Berichte No. 87-12, RWTH Aachen,
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Fachgruppe Informatik, Aachen, Fed. Rep. of Germany, 1987.
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\bibitem[Cha87]{chase-popl}
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David~R. Chase.
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\newblock An improvement to bottom up tree pattern matching.
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\newblock {\em Fourteenth Annual ACM Symposium on Principles of Programming
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\bibitem[FH91]{fraser-henry-spe-91}
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Christopher~W. Fraser and Robert~R. Henry.
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\newblock Hard-coding bottom-up code generation tables to save time and space.
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\newblock {\em Software---Practice\&Experience}, 21(1):1--12, January 1991.
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\bibitem[HC86]{hatcher-popl}
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Philip~J. Hatcher and Thomas~W. Christopher.
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\newblock {\em Thirteenth Annual ACM Symposium on Principles of Programming
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\bibitem[Hen89]{henry-budp}
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Robert~R. Henry.
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\newblock Encoding optimal pattern selection in a table-driven bottom-up
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tree-pattern matcher.
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\newblock Technical Report 89-02-04, University of Washington Computer Science
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Department, Seattle, WA, February 1989.
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\bibitem[HO82]{hoffmann-jacm}
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Christoph Hoffmann and Michael~J. O'Donnell.
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\newblock Pattern matching in trees.
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\newblock {\em Journal of the ACM}, 29(1):68--95, January 1982.
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\bibitem[Kro75]{kron-phd}
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H.~H. Kron.
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\newblock {\em Tree Templates and Subtree Transformational Grammars}.
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\newblock PhD thesis, UC Santa Cruz, December 1975.
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\bibitem[PL87]{pelegri-phd}
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Eduardo Pelegri-Llopart.
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\newblock {\em Tree Transformations in Compiler Systems}.
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\newblock PhD thesis, UC Berkeley, December 1987.
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\bibitem[PLG88]{pelegri-popl}
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Eduardo Pelegri-Llopart and Susan~L. Graham.
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\newblock Optimal code generation for expression trees: An application of
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\newblock {\em Fifteenth Annual ACM Symposium on Principles of Programming
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\bibitem[Pro91]{proebsting-91}
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\newblock Technical report, Department of Computer Sciences, University of
|
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Wisconsin, 1991.
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\end{thebibliography}
|
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|
|
\end{document}
|
|
|