check

book.tex

@@ -10146,30 +10146,30 @@ guaranteed that iteratively applying liveness analysis to all blocks
 in the program will eventually produce the least fixed point solution.
 
 Next let us consider dataflow analysis in general and discuss the
-generic work list algorithm (Figure~\ref{fig:generic-dataflow}).
+generic work list algorithm (Figure~\ref{fig:generic-dataflow}). 
 %
 The algorithm has four parameters: the control-flow graph \code{G}, a
 function \code{transfer} that applies the analysis to one block, the
 \code{bottom} and \code{join} operator for the lattice of abstract
-states.  The algorithm begins by creating the bottom mapping,
-represented by a hash table.  It then pushes all of the nodes in the
-control-flow graph onto the work list (a queue). The algorithm repeats
-the \code{while} loop as long as there are items in the work list. In
-each iteration, a node is popped from the work list and processed. The
-\code{input} for the node is computed by taking the join of the
-abstract states of all the predecessor nodes. The \code{transfer}
-function is then applied to obtain the \code{output} abstract
-state. If the output differs from the previous state for this block,
-the mapping for this block is updated and its successor nodes are
-pushed onto the work list.
-
-Note that the \code{analyze\_dataflow} function is formulated as a
+states. The \code{analyze\_dataflow} function is formulated as a
 \emph{forward} dataflow analysis, that is, the inputs to the transfer
 function come from the predecessor nodes in the control-flow
 graph. However, liveness analysis is a \emph{backward} dataflow
 analysis, so in that case one must supply the \code{analyze\_dataflow}
 function with the transpose of the control-flow graph.
 
+The algorithm begins by creating the bottom mapping, represented by a
+hash table.  It then pushes all of the nodes in the control-flow graph
+onto the work list (a queue). The algorithm repeats the \code{while}
+loop as long as there are items in the work list. In each iteration, a
+node is popped from the work list and processed. The \code{input} for
+the node is computed by taking the join of the abstract states of all
+the predecessor nodes. The \code{transfer} function is then applied to
+obtain the \code{output} abstract state. If the output differs from
+the previous state for this block, the mapping for this block is
+updated and its successor nodes are pushed onto the work list.
+
+
 \begin{figure}[tb]
 {\if\edition\racketEd    
 \begin{lstlisting}
@@ -10511,7 +10511,6 @@ control-flow graphs of the later may contain cycles.
 \fbox{
 \begin{minipage}{0.96\textwidth}
 \small
-{\if\edition\racketEd
 \[
 \begin{array}{l}
   \gray{\CvarASTRacket} \\ \hline
@@ -10522,10 +10521,6 @@ control-flow graphs of the later may contain cycles.
 \end{array}
 \end{array}
 \]
-\fi}
-{\if\edition\pythonEd
-UNDER CONSTRUCTION
-\fi}
 \end{minipage}
 }
 \caption{The abstract syntax of \LangCLoop{}, extending \LangCIf{} (Figure~\ref{fig:c1-syntax}).}