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Merge branch 'master' of github.com:IUCompilerCourse/Essentials-of-Compilation
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book.tex

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@@ -1328,7 +1328,7 @@ \section{Recursive Functions}
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[(Program '() e) (is_exp e)]
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[else #f]))
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(is_Lint (Program '() ast1_1)
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(is_Lint (Program '() ast1_1))
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(is_Lint (Program '()
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(Prim '* (list (Prim 'read '())
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(Prim '+ (list (Int 8)))))))
@@ -1769,7 +1769,7 @@ \section{Example Compiler: A Partial Evaluator}
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case Expr(value):
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return Expr(pe_exp(value))
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def pe_P_int(p):
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def pe_Lint(p):
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match p:
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case Module(body):
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new_body = [pe_stmt(s) for s in body]
@@ -2016,7 +2016,7 @@ \subsection{Extensible Interpreters via Method Overriding}
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of commonality between these interpreters. We want to write down the
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common parts just once instead of many times. A naive interpreter for
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\LangVar{} would handle the \racket{cases for variables and
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\code{let}} \python{case for variables} but dispatch to an
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\code{let}}\python{case for variables} but dispatch to an
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interpreter for \LangInt{} in the rest of the cases. The following
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code sketches this idea. (We explain the \code{env} parameter in
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section~\ref{sec:interp-Lvar}.)
@@ -14846,7 +14846,7 @@ \section{Challenge: Generational Collection}
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time proportional to all the live data. One way to reduce this
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overhead is to reduce how much data is inspected in each call to
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\code{collect}. In particular, researchers have observed that recently
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allocated data is more likely to become garbage then data that has
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allocated data is more likely to become garbage than data that has
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survived one or more previous calls to \code{collect}. This insight
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motivated the creation of \emph{generational garbage collectors}
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\index{subject}{generational garbage collector} that

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