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% Chapter Template
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% Main chapter title
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\chapter{Correctness of Bit-coded Algorithm without Simplification}
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\label{ChapterBitcoded1} % Change X to a consecutive number; for referencing this chapter elsewhere, use \ref{ChapterX}
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%Then we illustrate how the algorithm without bitcodes falls short for such aggressive
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%simplifications and therefore introduce our version of the bitcoded algorithm and
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%its correctness proof in
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%Chapter 3\ref{Chapter3}.
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\section*{Bit-coded Algorithm}
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Bits and bitcodes (lists of bits) are defined as:
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\begin{center}
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$b ::= 1 \mid 0 \qquad
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bs ::= [] \mid b::bs
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$
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\end{center}
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\noindent
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The $1$ and $0$ are not in bold in order to avoid
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confusion with the regular expressions $\ZERO$ and $\ONE$. Bitcodes (or
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bit-lists) can be used to encode values (or potentially incomplete values) in a
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compact form. This can be straightforwardly seen in the following
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coding function from values to bitcodes:
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\begin{center}
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\begin{tabular}{lcl}
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$\textit{code}(\Empty)$ & $\dn$ & $[]$\\
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$\textit{code}(\Char\,c)$ & $\dn$ & $[]$\\
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$\textit{code}(\Left\,v)$ & $\dn$ & $0 :: code(v)$\\
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$\textit{code}(\Right\,v)$ & $\dn$ & $1 :: code(v)$\\
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$\textit{code}(\Seq\,v_1\,v_2)$ & $\dn$ & $code(v_1) \,@\, code(v_2)$\\
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$\textit{code}(\Stars\,[])$ & $\dn$ & $[0]$\\
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$\textit{code}(\Stars\,(v\!::\!vs))$ & $\dn$ & $1 :: code(v) \;@\;
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code(\Stars\,vs)$
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\end{tabular}
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\end{center}
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\noindent
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Here $\textit{code}$ encodes a value into a bitcodes by converting
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$\Left$ into $0$, $\Right$ into $1$, and marks the start of a non-empty
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star iteration by $1$. The border where a local star terminates
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is marked by $0$. This coding is lossy, as it throws away the information about
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characters, and also does not encode the ``boundary'' between two
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sequence values. Moreover, with only the bitcode we cannot even tell
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whether the $1$s and $0$s are for $\Left/\Right$ or $\Stars$. The
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reason for choosing this compact way of storing information is that the
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relatively small size of bits can be easily manipulated and ``moved
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around'' in a regular expression. In order to recover values, we will
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need the corresponding regular expression as an extra information. This
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means the decoding function is defined as:
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%\begin{definition}[Bitdecoding of Values]\mbox{}
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\begin{center}
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\begin{tabular}{@{}l@{\hspace{1mm}}c@{\hspace{1mm}}l@{}}
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$\textit{decode}'\,bs\,(\ONE)$ & $\dn$ & $(\Empty, bs)$\\
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$\textit{decode}'\,bs\,(c)$ & $\dn$ & $(\Char\,c, bs)$\\
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$\textit{decode}'\,(0\!::\!bs)\;(r_1 + r_2)$ & $\dn$ &
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$\textit{let}\,(v, bs_1) = \textit{decode}'\,bs\,r_1\;\textit{in}\;
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(\Left\,v, bs_1)$\\
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$\textit{decode}'\,(1\!::\!bs)\;(r_1 + r_2)$ & $\dn$ &
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$\textit{let}\,(v, bs_1) = \textit{decode}'\,bs\,r_2\;\textit{in}\;
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(\Right\,v, bs_1)$\\
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$\textit{decode}'\,bs\;(r_1\cdot r_2)$ & $\dn$ &
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$\textit{let}\,(v_1, bs_1) = \textit{decode}'\,bs\,r_1\;\textit{in}$\\
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& & $\textit{let}\,(v_2, bs_2) = \textit{decode}'\,bs_1\,r_2$\\
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& & \hspace{35mm}$\textit{in}\;(\Seq\,v_1\,v_2, bs_2)$\\
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$\textit{decode}'\,(0\!::\!bs)\,(r^*)$ & $\dn$ & $(\Stars\,[], bs)$\\
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$\textit{decode}'\,(1\!::\!bs)\,(r^*)$ & $\dn$ &
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$\textit{let}\,(v, bs_1) = \textit{decode}'\,bs\,r\;\textit{in}$\\
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& & $\textit{let}\,(\Stars\,vs, bs_2) = \textit{decode}'\,bs_1\,r^*$\\
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& & \hspace{35mm}$\textit{in}\;(\Stars\,v\!::\!vs, bs_2)$\bigskip\\
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$\textit{decode}\,bs\,r$ & $\dn$ &
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$\textit{let}\,(v, bs') = \textit{decode}'\,bs\,r\;\textit{in}$\\
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& & $\textit{if}\;bs' = []\;\textit{then}\;\textit{Some}\,v\;
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\textit{else}\;\textit{None}$
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\end{tabular}
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\end{center}
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%\end{definition}
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Sulzmann and Lu's integrated the bitcodes into regular expressions to
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create annotated regular expressions \cite{Sulzmann2014}.
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\emph{Annotated regular expressions} are defined by the following
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grammar:%\comment{ALTS should have an $as$ in the definitions, not just $a_1$ and $a_2$}
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\begin{center}
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\begin{tabular}{lcl}
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$\textit{a}$ & $::=$ & $\ZERO$\\
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& $\mid$ & $_{bs}\ONE$\\
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& $\mid$ & $_{bs}{\bf c}$\\
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& $\mid$ & $_{bs}\sum\,as$\\
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& $\mid$ & $_{bs}a_1\cdot a_2$\\
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& $\mid$ & $_{bs}a^*$
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\end{tabular}
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\end{center}
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%(in \textit{ALTS})
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\noindent
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where $bs$ stands for bitcodes, $a$ for $\mathbf{a}$nnotated regular
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expressions and $as$ for a list of annotated regular expressions.
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The alternative constructor($\sum$) has been generalized to
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accept a list of annotated regular expressions rather than just 2.
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We will show that these bitcodes encode information about
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the (POSIX) value that should be generated by the Sulzmann and Lu
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algorithm.
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To do lexing using annotated regular expressions, we shall first
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transform the usual (un-annotated) regular expressions into annotated
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regular expressions. This operation is called \emph{internalisation} and
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defined as follows:
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%\begin{definition}
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\begin{center}
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\begin{tabular}{lcl}
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$(\ZERO)^\uparrow$ & $\dn$ & $\ZERO$\\
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$(\ONE)^\uparrow$ & $\dn$ & $_{[]}\ONE$\\
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$(c)^\uparrow$ & $\dn$ & $_{[]}{\bf c}$\\
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$(r_1 + r_2)^\uparrow$ & $\dn$ &
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$_{[]}\sum[\textit{fuse}\,[0]\,r_1^\uparrow,\,
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\textit{fuse}\,[1]\,r_2^\uparrow]$\\
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$(r_1\cdot r_2)^\uparrow$ & $\dn$ &
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$_{[]}r_1^\uparrow \cdot r_2^\uparrow$\\
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$(r^*)^\uparrow$ & $\dn$ &
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$_{[]}(r^\uparrow)^*$\\
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\end{tabular}
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\end{center}
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%\end{definition}
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\noindent
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We use up arrows here to indicate that the basic un-annotated regular
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expressions are ``lifted up'' into something slightly more complex. In the
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fourth clause, $\textit{fuse}$ is an auxiliary function that helps to
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attach bits to the front of an annotated regular expression. Its
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definition is as follows:
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\begin{center}
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\begin{tabular}{lcl}
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$\textit{fuse}\;bs \; \ZERO$ & $\dn$ & $\ZERO$\\
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$\textit{fuse}\;bs\; _{bs'}\ONE$ & $\dn$ &
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$_{bs @ bs'}\ONE$\\
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$\textit{fuse}\;bs\;_{bs'}{\bf c}$ & $\dn$ &
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$_{bs@bs'}{\bf c}$\\
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$\textit{fuse}\;bs\,_{bs'}\sum\textit{as}$ & $\dn$ &
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$_{bs@bs'}\sum\textit{as}$\\
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$\textit{fuse}\;bs\; _{bs'}a_1\cdot a_2$ & $\dn$ &
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$_{bs@bs'}a_1 \cdot a_2$\\
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$\textit{fuse}\;bs\,_{bs'}a^*$ & $\dn$ &
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$_{bs @ bs'}a^*$
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\end{tabular}
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\end{center}
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\noindent
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After internalising the regular expression, we perform successive
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derivative operations on the annotated regular expressions. This
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derivative operation is the same as what we had previously for the
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basic regular expressions, except that we beed to take care of
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the bitcodes:
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\iffalse
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%\begin{definition}{bder}
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\begin{center}
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\begin{tabular}{@{}lcl@{}}
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$(\textit{ZERO})\,\backslash c$ & $\dn$ & $\textit{ZERO}$\\
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$(\textit{ONE}\;bs)\,\backslash c$ & $\dn$ & $\textit{ZERO}$\\
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$(\textit{CHAR}\;bs\,d)\,\backslash c$ & $\dn$ &
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$\textit{if}\;c=d\; \;\textit{then}\;
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\textit{ONE}\;bs\;\textit{else}\;\textit{ZERO}$\\
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$(\textit{ALTS}\;bs\,as)\,\backslash c$ & $\dn$ &
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$\textit{ALTS}\;bs\,(map (\backslash c) as)$\\
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$(\textit{SEQ}\;bs\,a_1\,a_2)\,\backslash c$ & $\dn$ &
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$\textit{if}\;\textit{bnullable}\,a_1$\\
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& &$\textit{then}\;\textit{ALTS}\,bs\,List((\textit{SEQ}\,[]\,(a_1\,\backslash c)\,a_2),$\\
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& &$\phantom{\textit{then}\;\textit{ALTS}\,bs\,}(\textit{fuse}\,(\textit{bmkeps}\,a_1)\,(a_2\,\backslash c)))$\\
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& &$\textit{else}\;\textit{SEQ}\,bs\,(a_1\,\backslash c)\,a_2$\\
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$(\textit{STAR}\,bs\,a)\,\backslash c$ & $\dn$ &
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$\textit{SEQ}\;bs\,(\textit{fuse}\, [\Z] (r\,\backslash c))\,
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(\textit{STAR}\,[]\,r)$
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\end{tabular}
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\end{center}
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%\end{definition}
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\begin{center}
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\begin{tabular}{@{}lcl@{}}
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$(\textit{ZERO})\,\backslash c$ & $\dn$ & $\textit{ZERO}$\\
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$(_{bs}\textit{ONE})\,\backslash c$ & $\dn$ & $\textit{ZERO}$\\
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$(_{bs}\textit{CHAR}\;d)\,\backslash c$ & $\dn$ &
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$\textit{if}\;c=d\; \;\textit{then}\;
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_{bs}\textit{ONE}\;\textit{else}\;\textit{ZERO}$\\
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$(_{bs}\textit{ALTS}\;\textit{as})\,\backslash c$ & $\dn$ &
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$_{bs}\textit{ALTS}\;(\textit{as}.\textit{map}(\backslash c))$\\
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$(_{bs}\textit{SEQ}\;a_1\,a_2)\,\backslash c$ & $\dn$ &
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$\textit{if}\;\textit{bnullable}\,a_1$\\
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& &$\textit{then}\;_{bs}\textit{ALTS}\,List((_{[]}\textit{SEQ}\,(a_1\,\backslash c)\,a_2),$\\
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& &$\phantom{\textit{then}\;_{bs}\textit{ALTS}\,}(\textit{fuse}\,(\textit{bmkeps}\,a_1)\,(a_2\,\backslash c)))$\\
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& &$\textit{else}\;_{bs}\textit{SEQ}\,(a_1\,\backslash c)\,a_2$\\
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$(_{bs}\textit{STAR}\,a)\,\backslash c$ & $\dn$ &
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$_{bs}\textit{SEQ}\;(\textit{fuse}\, [0] \; r\,\backslash c )\,
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(_{bs}\textit{STAR}\,[]\,r)$
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\end{tabular}
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\end{center}
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%\end{definition}
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\fi
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\begin{center}
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\begin{tabular}{@{}lcl@{}}
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$(\ZERO)\,\backslash c$ & $\dn$ & $\ZERO$\\
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$(_{bs}\ONE)\,\backslash c$ & $\dn$ & $\ZERO$\\
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$(_{bs}{\bf d})\,\backslash c$ & $\dn$ &
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$\textit{if}\;c=d\; \;\textit{then}\;
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_{bs}\ONE\;\textit{else}\;\ZERO$\\
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$(_{bs}\sum \;\textit{as})\,\backslash c$ & $\dn$ &
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$_{bs}\sum\;(\textit{map} (\_\backslash c) as )$\\
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$(_{bs}\;a_1\cdot a_2)\,\backslash c$ & $\dn$ &
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$\textit{if}\;\textit{bnullable}\,a_1$\\
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& &$\textit{then}\;_{bs}\sum\,[(_{[]}\,(a_1\,\backslash c)\cdot\,a_2),$\\
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& &$\phantom{\textit{then},\;_{bs}\sum\,}(\textit{fuse}\,(\textit{bmkeps}\,a_1)\,(a_2\,\backslash c))]$\\
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& &$\textit{else}\;_{bs}\,(a_1\,\backslash c)\cdot a_2$\\
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$(_{bs}a^*)\,\backslash c$ & $\dn$ &
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$_{bs}(\textit{fuse}\, [0] \; r\,\backslash c)\cdot
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(_{[]}r^*))$
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\end{tabular}
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\end{center}
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%\end{definition}
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\noindent
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For instance, when we do derivative of $_{bs}a^*$ with respect to c,
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we need to unfold it into a sequence,
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and attach an additional bit $0$ to the front of $r \backslash c$
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to indicate one more star iteration. Also the sequence clause
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is more subtle---when $a_1$ is $\textit{bnullable}$ (here
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\textit{bnullable} is exactly the same as $\textit{nullable}$, except
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that it is for annotated regular expressions, therefore we omit the
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definition). Assume that $\textit{bmkeps}$ correctly extracts the bitcode for how
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$a_1$ matches the string prior to character $c$ (more on this later),
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then the right branch of alternative, which is $\textit{fuse} \; \bmkeps \; a_1 (a_2
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\backslash c)$ will collapse the regular expression $a_1$(as it has
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already been fully matched) and store the parsing information at the
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head of the regular expression $a_2 \backslash c$ by fusing to it. The
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bitsequence $\textit{bs}$, which was initially attached to the
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first element of the sequence $a_1 \cdot a_2$, has
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now been elevated to the top-level of $\sum$, as this information will be
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needed whichever way the sequence is matched---no matter whether $c$ belongs
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to $a_1$ or $ a_2$. After building these derivatives and maintaining all
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the lexing information, we complete the lexing by collecting the
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bitcodes using a generalised version of the $\textit{mkeps}$ function
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for annotated regular expressions, called $\textit{bmkeps}$:
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%\begin{definition}[\textit{bmkeps}]\mbox{}
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\begin{center}
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\begin{tabular}{lcl}
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$\textit{bmkeps}\,(_{bs}\ONE)$ & $\dn$ & $bs$\\
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$\textit{bmkeps}\,(_{bs}\sum a::\textit{as})$ & $\dn$ &
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$\textit{if}\;\textit{bnullable}\,a$\\
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& &$\textit{then}\;bs\,@\,\textit{bmkeps}\,a$\\
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& &$\textit{else}\;bs\,@\,\textit{bmkeps}\,(_{bs}\sum \textit{as})$\\
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$\textit{bmkeps}\,(_{bs} a_1 \cdot a_2)$ & $\dn$ &
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$bs \,@\,\textit{bmkeps}\,a_1\,@\, \textit{bmkeps}\,a_2$\\
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$\textit{bmkeps}\,(_{bs}a^*)$ & $\dn$ &
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$bs \,@\, [0]$
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\end{tabular}
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\end{center}
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%\end{definition}
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\noindent
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This function completes the value information by travelling along the
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path of the regular expression that corresponds to a POSIX value and
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collecting all the bitcodes, and using $S$ to indicate the end of star
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iterations. If we take the bitcodes produced by $\textit{bmkeps}$ and
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decode them, we get the value we expect. The corresponding lexing
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algorithm looks as follows:
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\begin{center}
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\begin{tabular}{lcl}
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$\textit{blexer}\;r\,s$ & $\dn$ &
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$\textit{let}\;a = (r^\uparrow)\backslash s\;\textit{in}$\\
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& & $\;\;\textit{if}\; \textit{bnullable}(a)$\\
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& & $\;\;\textit{then}\;\textit{decode}\,(\textit{bmkeps}\,a)\,r$\\
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& & $\;\;\textit{else}\;\textit{None}$
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\end{tabular}
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\end{center}
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\noindent
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In this definition $\_\backslash s$ is the generalisation of the derivative
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operation from characters to strings (just like the derivatives for un-annotated
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regular expressions).
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Now we introduce the simplifications, which is why we introduce the
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bitcodes in the first place.
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\subsection*{Simplification Rules}
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This section introduces aggressive (in terms of size) simplification rules
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on annotated regular expressions
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to keep derivatives small. Such simplifications are promising
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as we have
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generated test data that show
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that a good tight bound can be achieved. We could only
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partially cover the search space as there are infinitely many regular
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expressions and strings.
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One modification we introduced is to allow a list of annotated regular
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expressions in the $\sum$ constructor. This allows us to not just
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delete unnecessary $\ZERO$s and $\ONE$s from regular expressions, but
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also unnecessary ``copies'' of regular expressions (very similar to
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simplifying $r + r$ to just $r$, but in a more general setting). Another
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modification is that we use simplification rules inspired by Antimirov's
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work on partial derivatives. They maintain the idea that only the first
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``copy'' of a regular expression in an alternative contributes to the
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calculation of a POSIX value. All subsequent copies can be pruned away from
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the regular expression. A recursive definition of our simplification function
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that looks somewhat similar to our Scala code is given below:
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%\comment{Use $\ZERO$, $\ONE$ and so on.
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%Is it $ALTS$ or $ALTS$?}\\
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\begin{center}
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\begin{tabular}{@{}lcl@{}}
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$\textit{simp} \; (_{bs}a_1\cdot a_2)$ & $\dn$ & $ (\textit{simp} \; a_1, \textit{simp} \; a_2) \; \textit{match} $ \\
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&&$\quad\textit{case} \; (\ZERO, \_) \Rightarrow \ZERO$ \\
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&&$\quad\textit{case} \; (\_, \ZERO) \Rightarrow \ZERO$ \\
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&&$\quad\textit{case} \; (\ONE, a_2') \Rightarrow \textit{fuse} \; bs \; a_2'$ \\
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&&$\quad\textit{case} \; (a_1', \ONE) \Rightarrow \textit{fuse} \; bs \; a_1'$ \\
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&&$\quad\textit{case} \; (a_1', a_2') \Rightarrow _{bs}a_1' \cdot a_2'$ \\
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$\textit{simp} \; (_{bs}\sum \textit{as})$ & $\dn$ & $\textit{distinct}( \textit{flatten} ( \textit{map} \; simp \; as)) \; \textit{match} $ \\
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&&$\quad\textit{case} \; [] \Rightarrow \ZERO$ \\
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&&$\quad\textit{case} \; a :: [] \Rightarrow \textit{fuse bs a}$ \\
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&&$\quad\textit{case} \; as' \Rightarrow _{bs}\sum \textit{as'}$\\
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$\textit{simp} \; a$ & $\dn$ & $\textit{a} \qquad \textit{otherwise}$
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\end{tabular}
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\end{center}
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\noindent
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The simplification does a pattern matching on the regular expression.
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When it detected that the regular expression is an alternative or
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sequence, it will try to simplify its child regular expressions
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recursively and then see if one of the children turns into $\ZERO$ or
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$\ONE$, which might trigger further simplification at the current level.
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The most involved part is the $\sum$ clause, where we use two
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auxiliary functions $\textit{flatten}$ and $\textit{distinct}$ to open up nested
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alternatives and reduce as many duplicates as possible. Function
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$\textit{distinct}$ keeps the first occurring copy only and removes all later ones
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when detected duplicates. Function $\textit{flatten}$ opens up nested $\sum$s.
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Its recursive definition is given below:
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\begin{center}
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\begin{tabular}{@{}lcl@{}}
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$\textit{flatten} \; (_{bs}\sum \textit{as}) :: \textit{as'}$ & $\dn$ & $(\textit{map} \;
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(\textit{fuse}\;bs)\; \textit{as}) \; @ \; \textit{flatten} \; as' $ \\
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$\textit{flatten} \; \ZERO :: as'$ & $\dn$ & $ \textit{flatten} \; \textit{as'} $ \\
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$\textit{flatten} \; a :: as'$ & $\dn$ & $a :: \textit{flatten} \; \textit{as'}$ \quad(otherwise)
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\end{tabular}
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\end{center}
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\noindent
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Here $\textit{flatten}$ behaves like the traditional functional programming flatten
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function, except that it also removes $\ZERO$s. Or in terms of regular expressions, it
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removes parentheses, for example changing $a+(b+c)$ into $a+b+c$.
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Having defined the $\simp$ function,
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we can use the previous notation of natural
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extension from derivative w.r.t.~character to derivative
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w.r.t.~string:%\comment{simp in the [] case?}
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\begin{center}
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\begin{tabular}{lcl}
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$r \backslash_{simp} (c\!::\!s) $ & $\dn$ & $(r \backslash_{simp}\, c) \backslash_{simp}\, s$ \\
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$r \backslash_{simp} [\,] $ & $\dn$ & $r$
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\end{tabular}
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\end{center}
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\noindent
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to obtain an optimised version of the algorithm:
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\begin{center}
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\begin{tabular}{lcl}
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$\textit{blexer\_simp}\;r\,s$ & $\dn$ &
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$\textit{let}\;a = (r^\uparrow)\backslash_{simp}\, s\;\textit{in}$\\
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& & $\;\;\textit{if}\; \textit{bnullable}(a)$\\
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& & $\;\;\textit{then}\;\textit{decode}\,(\textit{bmkeps}\,a)\,r$\\
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& & $\;\;\textit{else}\;\textit{None}$
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390 |
\end{tabular}
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\end{center}
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|
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\noindent
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394 |
This algorithm keeps the regular expression size small, for example,
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with this simplification our previous $(a + aa)^*$ example's 8000 nodes
|
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will be reduced to just 6 and stays constant, no matter how long the
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|
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input string is.
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|
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409 |
%-----------------------------------
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|
410 |
% SUBSECTION 1
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|
411 |
%-----------------------------------
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412 |
\section{Specifications of Some Helper Functions}
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|
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Here we give some functions' definitions,
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|
414 |
which we will use later.
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\begin{center}
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|
416 |
\begin{tabular}{ccc}
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|
417 |
$\retrieve \; \ACHAR \, \textit{bs} \, c \; \Char(c) = \textit{bs}$
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|
418 |
\end{tabular}
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|
419 |
\end{center}
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|
420 |
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|
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%----------------------------------------------------------------------------------------
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|
423 |
% SECTION correctness proof
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|
424 |
%----------------------------------------------------------------------------------------
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|
425 |
\section{Correctness of Bit-coded Algorithm (Without Simplification)}
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|
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We now give the proof the correctness of the algorithm with bit-codes.
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|
427 |
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|
428 |
Ausaf and Urban cleverly defined an auxiliary function called $\flex$,
|
|
429 |
defined as
|
|
430 |
\[
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|
431 |
\flex \; r \; f \; [] \; v \; = \; f\; v
|
|
432 |
\flex \; r \; f \; c :: s \; v = \flex r \; \lambda v. \, f (\inj \; r\; c\; v)\; s \; v
|
|
433 |
\]
|
|
434 |
which accumulates the characters that needs to be injected back,
|
|
435 |
and does the injection in a stack-like manner (last taken derivative first injected).
|
|
436 |
$\flex$ is connected to the $\lexer$:
|
|
437 |
\begin{lemma}
|
|
438 |
$\flex \; r \; \textit{id}\; s \; \mkeps (r\backslash s) = \lexer \; r \; s$
|
|
439 |
\end{lemma}
|
|
440 |
$\flex$ provides us a bridge between $\lexer$ and $\blexer$.
|
|
441 |
What is even better about $\flex$ is that it allows us to
|
|
442 |
directly operate on the value $\mkeps (r\backslash v)$,
|
|
443 |
which is pivotal in the definition of $\lexer $ and $\blexer$, but not visible as an argument.
|
|
444 |
When the value created by $\mkeps$ becomes available, one can
|
|
445 |
prove some stepwise properties of lexing nicely:
|
|
446 |
\begin{lemma}\label{flexStepwise}
|
|
447 |
$\textit{flex} \; r \; f \; s@[c] \; v= \flex \; r \; f\; s \; (\inj \; (r\backslash s) \; c \; v) $
|
|
448 |
\end{lemma}
|
|
449 |
|
|
450 |
And for $\blexer$ we have a function with stepwise properties like $\flex$ as well,
|
|
451 |
called $\retrieve$\ref{retrieveDef}.
|
|
452 |
$\retrieve$ takes bit-codes from annotated regular expressions
|
|
453 |
guided by a value.
|
|
454 |
$\retrieve$ is connected to the $\blexer$ in the following way:
|
|
455 |
\begin{lemma}\label{blexer_retrieve}
|
|
456 |
$\blexer \; r \; s = \decode \; (\retrieve \; (\internalise \; r) \; (\mkeps \; (r \backslash s) )) \; r$
|
|
457 |
\end{lemma}
|
|
458 |
If you take derivative of an annotated regular expression,
|
|
459 |
you can $\retrieve$ the same bit-codes as before the derivative took place,
|
|
460 |
provided that you use the corresponding value:
|
|
461 |
|
|
462 |
\begin{lemma}\label{retrieveStepwise}
|
|
463 |
$\retrieve \; (r \backslash c) \; v= \retrieve \; r \; (\inj \; r\; c\; v)$
|
|
464 |
\end{lemma}
|
|
465 |
The other good thing about $\retrieve$ is that it can be connected to $\flex$:
|
|
466 |
%centralLemma1
|
|
467 |
\begin{lemma}\label{flex_retrieve}
|
|
468 |
$\flex \; r \; \textit{id}\; s\; v = \decode \; (\retrieve \; (r\backslash s )\; v) \; r$
|
|
469 |
\end{lemma}
|
|
470 |
\begin{proof}
|
|
471 |
By induction on $s$. The induction tactic is reverse induction on strings.
|
|
472 |
$v$ is allowed to be arbitrary.
|
|
473 |
The crucial point is to rewrite
|
|
474 |
\[
|
|
475 |
\retrieve \; (r \backslash s@[c]) \; \mkeps (r \backslash s@[c])
|
|
476 |
\]
|
|
477 |
as
|
|
478 |
\[
|
|
479 |
\retrieve \; (r \backslash s) \; (\inj \; (r \backslash s) \; c\; \mkeps (r \backslash s@[c]))
|
|
480 |
\].
|
|
481 |
This enables us to equate
|
|
482 |
\[
|
|
483 |
\retrieve \; (r \backslash s@[c]) \; \mkeps (r \backslash s@[c])
|
|
484 |
\]
|
|
485 |
with
|
|
486 |
\[
|
|
487 |
\flex \; r \; \textit{id} \; s \; (\inj \; (r\backslash s) \; c\; (\mkeps (r\backslash s@[c])))
|
|
488 |
\],
|
|
489 |
which in turn can be rewritten as
|
|
490 |
\[
|
|
491 |
\flex \; r \; \textit{id} \; s@[c] \; (\mkeps (r\backslash s@[c]))
|
|
492 |
\].
|
|
493 |
\end{proof}
|
|
494 |
|
|
495 |
With the above lemma we can now link $\flex$ and $\blexer$.
|
|
496 |
|
|
497 |
\begin{lemma}\label{flex_blexer}
|
|
498 |
$\textit{flex} \; r \; \textit{id} \; s \; \mkeps(r \backslash s) = \blexer \; r \; s$
|
|
499 |
\end{lemma}
|
|
500 |
\begin{proof}
|
|
501 |
Using two of the above lemmas: \ref{flex_retrieve} and \ref{blexer_retrieve}.
|
|
502 |
\end{proof}
|
|
503 |
Finally
|
|
504 |
|
|
505 |
|
530
|
506 |
|