Formatting and space.

.gitignore

@@ -9,3 +9,4 @@ pdfa.xmpi
 main.bbl
 main.blg
 vizier.db
+/_minted-main

main.tex

@@ -2,6 +2,7 @@
 %\documentclass{vldb}
 
 \settopmatter{printacmref=false}
+\setcopyright{none}
 
 \usepackage{hyperref}
 \usepackage[a-1b]{pdfx}
@@ -49,7 +50,7 @@
 
 \newcommand{\systemname}{Workbook\xspace}
 
-\newcommand{\TheTitle}{Coarse-Grained Dataflow Provenance}
+\newcommand{\TheTitle}{Incremental Provenance}
 
 \pagestyle{plain}
 

sections/experiments.tex

@@ -7,7 +7,7 @@ Parallelizing cell execution requires an ICE architecture, which comes at the co
 In this section, we assess that cost.
 
 All experiments were run on a XX GHz, XX core Intel Xeon with XX GB RAM running XX Linux\OK{Boris, Nachiket, can you fill this in?}.
-The provenance aware scheduler was integrated into Vizier 1.2\footnote{https://github.com/VizierDB/vizier-scala} --- our experiments use a lightly modified version with support for importing Jupyter notebooks, and the related \texttt{-X PARALLEL-PYTHON} experimental option.  
+The provenance aware scheduler was integrated into Vizier 1.2\footnote{\url{https://github.com/VizierDB/vizier-scala}} --- our experiments use a lightly modified version with support for importing Jupyter notebooks, and the related \texttt{-X PARALLEL-PYTHON} experimental option.  
 As Vizier relies on Apache Spark, we prefix all notebooks under test with a single reader and writer cell to force initialization of e.g., Spark's HDFS module.  These are not included in timing results.
 
 \begin{figure*}

sections/import.tex

@@ -20,9 +20,10 @@ For example, python's \texttt{import} statement simply declares imported modules
 Thus, references to the module's functions within a function or class definition create transitive dependencies.
 When the traversal visits a function or class declaration statement, we record
 
-An additional complication arises from python's scope capture semantics.
+\begin{figure}
-When a function (or class) is declared, it records a reference to all enclosing scopes.  Consider the following example code:
+  \begin{center}
-\begin{lstlisting}
+  \begin{subfigure}{0.45\columnwidth}
+\begin{minted}{python}
 def foo():
   print(a)
 a = 1
@@ -31,21 +32,29 @@ def bar():
   a = 2
   foo()
 bar()  # Prints '1'
-\end{lstlisting}
+\end{minted}
-
+  \end{subfigure}
-\begin{lstlisting}
+  \begin{subfigure}{0.5\columnwidth}
+\begin{minted}{python}
 def foo():
-  a = 2
   def bar():
     print(a)
+  a = 2
   return bar
 bar = foo()
 bar()  # Prints '2'
 a = 1
 bar()  # Prints '2'
-\end{lstlisting}
+\end{minted}
+  \end{subfigure}
+  \end{center}
+  \label{fig:scoping}
+  \caption{Scope capture in python happens at function definition, but captured scopes remain mutable.}
+\end{figure}
 
-In the latter instance, when \texttt{bar} is declared, it `captures' the scope of \texttt{foo}, in which \texttt{a = 2}, and overrides assignment in the global scope.
+An additional complication arises from python's scope capture semantics.
+When a function (or class) is declared, it records a reference to all enclosing scopes.  Consider the following example code in \Cref{fig:scoping}.
+In the latter code block, when \texttt{bar} is declared, it `captures' the scope of \texttt{foo}, in which \texttt{a = 2}, and overrides assignment in the global scope.
 In the former instance, conversely, \texttt{bar}'s assignment to \texttt{a} happens in its own scope, and so the invocation of \texttt{foo} reads the instance of \texttt{a} in the global scope.
 
 \tinysection{Coarse-Grained Data Flow}

sections/introduction.tex

@@ -27,8 +27,8 @@ We then show generality by discussing the process for importing Jupyter notebook
 \begin{figure}
 % \includegraphics[width=\columnwidth]{graphics/depth_vs_cellcount.vega-lite.pdf}
 \includegraphics[width=0.8\columnwidth]{graphics/depth_vs_cellcount-averaged.vega-lite.pdf}
-\caption{Notebook size versus workflow depth in a collection of notebooks scraped from github~\cite{DBLP:journals/ese/PimentelMBF21}: On average, only one out of every 4 notebook cells must be run serially.}
+\caption{Notebook size versus workflow depth in a collection of notebooks scraped from github~\cite{DBLP:journals/ese/PimentelMBF21}: On average, only one out of every 4 notebook cells has serial dependencies.}
-\label{fig:parallelismSurvey}
+\label{fig:parallelismSurvey} 
 \end{figure}
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