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\section*{Handout 4 (Sulzmann \& Lu Algorithm)}

So far our algorithm based on derivatives was only able to say

yes or no depending on whether a string was matched by regular

expression or not. Often a more interesting question is to

find out \emph{how} a regular expression matched a string?

Answering this question will help us with the problem we are

after, namely tokenising an input string. The algorithm we

will be looking at for this was designed by Sulzmann \& Lu in

a rather recent paper. A link to it is provided on KEATS, in

case you are interested.\footnote{In my humble opinion this is

an interesting instance of the research literature: it

contains a very neat idea, but its presentation is rather

sloppy. In earlier versions of their paper, students and I

found several rather annoying typos in their examples and

definitions.}

In order to give an answer for how a regular expression

matched a string, Sulzmann and Lu introduce \emph{values}. A

value will be the output of the algorithm whenever the regular

expression matches the string. If not, an error will be

raised. Since the first phase of the algorithm by Sulzmann \&

Lu is identical to the derivative based matcher from the first

coursework, the function $nullable$ will be used to decide

whether as string is matched by a regular expression. If

$nullable$ says yes, then values are constructed that reflect

how the regular expression matched the string. The definitions

for regular expressions $r$ and values $v$ is shown next to

each other below:

\begin{center}

\begin{tabular}{cc}

\begin{tabular}{@{}rrl@{}}

\multicolumn{3}{c}{regular expressions}\\

  $r$ & $::=$  & $\varnothing$\\

      & $\mid$ & $\epsilon$   \\

      & $\mid$ & $c$          \\

      & $\mid$ & $r_1 \cdot r_2$\\

      & $\mid$ & $r_1 + r_2$   \\

  \\

      & $\mid$ & $r^*$         \\

\end{tabular}

&

\begin{tabular}{@{\hspace{0mm}}rrl@{}}

\multicolumn{3}{c}{values}\\

   $v$ & $::=$  & \\

      &        & $Empty$   \\

      & $\mid$ & $Char(c)$          \\

      & $\mid$ & $Seq(v_1,v_2)$\\

      & $\mid$ & $Left(v)$   \\

      & $\mid$ & $Right(v)$  \\

      & $\mid$ & $[v_1,\ldots\,v_n]$ \\

\end{tabular}

\end{tabular}

\end{center}

\noindent The point is that there is a very strong

correspondence between them. There is no value for the

$\varnothing$ regular expression, since it does not match any

string. Otherwise there is exactly one value corresponding to

each regular expression with the exception of $r_1 + r_2$

where there are two values, namely $Left(v)$ and $Right(v)$

corresponding to the two alternatives. Note that $r^*$ is

associated with a list of values, one for each copy of $r$

that was needed to match the string. This means we might also

return the empty list $[]$, if no copy was needed.

Graphically the algorithm by Sulzmann \& Lu can be represneted

by the picture in Figure~\ref{Sulz} where the path from the

left to the right involving $der/nullable$ is the first phase

of the algorithm and $mkeps/inj$, the path from right to left,

the second phase. This picture shows the steps required when a

regular expression, say $r_1$, matches the string $abc$. We

first build the three derivatives (according to $a$, $b$ and

$c$). We then use $nullable$ to find out whether the resulting

regular expression can match the empty string. If yes we call

the function $mkeps$.

\begin{figure}[t]

\begin{center}

\begin{tikzpicture}[scale=2,node distance=1.2cm,

                    every node/.style={minimum size=7mm}]

\node (r1)  {$r_1$};

\node (r2) [right=of r1]{$r_2$};

\draw[->,line width=1mm](r1)--(r2) node[above,midway] {$der\,a$};

\node (r3) [right=of r2]{$r_3$};

\draw[->,line width=1mm](r2)--(r3) node[above,midway] {$der\,b$};

\node (r4) [right=of r3]{$r_4$};

\draw[->,line width=1mm](r3)--(r4) node[above,midway] {$der\,c$};

\draw (r4) node[anchor=west] {\;\raisebox{3mm}{$nullable$}};

\node (v4) [below=of r4]{$v_4$};

\draw[->,line width=1mm](r4) -- (v4);

\node (v3) [left=of v4] {$v_3$};

\draw[->,line width=1mm](v4)--(v3) node[below,midway] {$inj\,c$};

\node (v2) [left=of v3]{$v_2$};

\draw[->,line width=1mm](v3)--(v2) node[below,midway] {$inj\,b$};

\node (v1) [left=of v2] {$v_1$};

\draw[->,line width=1mm](v2)--(v1) node[below,midway] {$inj\,a$};

\draw (r4) node[anchor=north west] {\;\raisebox{-8mm}{$mkeps$}};

\end{tikzpicture}

\end{center}

\caption{The two phases of the algorithm by Sulzmann \& Lu.

\label{Sulz}}

\end{figure}

The $mkeps$ function calculates a value for how a regular

expression has matched the empty string. Its definition

is as follows:

\begin{center}

\begin{tabular}{lcl}

  $mkeps(\epsilon)$       & $\dn$ & $Empty$\\

  $mkeps(r_1 + r_2)$      & $\dn$ & if $nullable(r_1)$  \\

                          &       & then $Left(mkeps(r_1))$\\

                          &       & else $Right(mkeps(r_2))$\\

  $mkeps(r_1 \cdot r_2)$  & $\dn$ & $Seq(mkeps(r_1),mkeps(r_2))$\\

  $mkeps(r^*)$            & $\dn$ & $[]$  \\

\end{tabular}

\end{center}

\noindent There are no cases for $\epsilon$ and $c$, since

these regular expression cannot match the empty string. Note

also that in case of alternatives we give preference to the

regular expression on the left-hand side. This will become

important later on.

The second phase of the algorithm is organised recursively

such that it will calculate a value for how the derivative

regular expression has matched a string whose first character

has been chopped off. Now we need a function that reverses

this ``chopping off'' for values. The corresponding function

is called $inj$ for injection. This function takes three

arguments: the first one is a regular expression for which we

want to calculate the value, the second is the character we

want to inject and the third argument is the value where we

will inject the character. The result of this function is a

new value. The definition of $inj$ is as follows: 

\begin{center}

\begin{tabular}{l@{\hspace{1mm}}c@{\hspace{1mm}}l}

  $inj\,(c)\,c\,Empty$            & $\dn$  & $Char\,c$\\

  $inj\,(r_1 + r_2)\,c\,Left(v)$  & $\dn$  & $Left(inj\,r_1\,c\,v)$\\

  $inj\,(r_1 + r_2)\,c\,Right(v)$ & $\dn$  & $Right(inj\,r_2\,c\,v)$\\

  $inj\,(r_1 \cdot r_2)\,c\,Seq(v_1,v_2)$ & $\dn$  & $Seq(inj\,r_1\,c\,v_1,v_2)$\\

  $inj\,(r_1 \cdot r_2)\,c\,Left(Seq(v_1,v_2))$ & $\dn$  & $Seq(inj\,r_1\,c\,v_1,v_2)$\\

  $inj\,(r_1 \cdot r_2)\,c\,Right(v)$ & $\dn$  & $Seq(mkeps(r_1),inj\,r_2\,c\,v)$\\

  $inj\,(r^*)\,c\,Seq(v,vs)$         & $\dn$  & $inj\,r\,c\,v\,::\,vs$\\

\end{tabular}

\end{center}

\noindent This definition is by recursion on the regular

expression and by analysing the shape of the values. Therefore

there are, for example, three cases for sequnece regular

expressions. The last clause for the star regular expression

returns a list where the first element is $inj\,r\,c\,v$ and

the other elements are $vs$. That mean $\_\,::\,\_$ should be 

read as list cons.

To understand what is going on, it might be best to do some

example calculations and compare with Figure~\ref{Sulz}. For

this note that we have not yet dealt with the need of

simplifying regular expressions (this will be a topic on its

own later). Suppose the regular expression is $a \cdot (b

\cdot c)$ and the input string is $abc$. The derivatives from

the first phase are as follows:

\begin{center}

\begin{tabular}{ll}

$r_1$: & $a \cdot (b \cdot c)$\\

$r_2$: & $\epsilon \cdot (b \cdot c)$\\

$r_3$: & $(\varnothing \cdot (b \cdot c)) + (\epsilon \cdot c)$\\

$r_4$: & $(\varnothing \cdot (b \cdot c)) + ((\varnothing \cdot c) + \epsilon)$\\

\end{tabular}

\end{center}

\noindent According to the simple algorithm, we would test

whether $r_4$ is nullable, which in this case it is. This

means we can use the function $mkeps$ to calculate a value for

how $r_4$ was able to match the empty string. Remember that

this function gives preference for alternatives on the

left-hand side. However there is only $\epsilon$ on the very

right-hand side of $r_4$ that matches the empty string.

Therefore $mkeps$ returns the value

\begin{center}

$v_4:\;Right(Right(Empty))$

\end{center}

\noindent The point is that from this value we can directly

read off which part of $r_4$ matched the empty string. Next we

have to ``inject'' the last character, that is $c$ in the

running example, into this value $v_4$ in order to calculate

how $r_3$ could have matched the string $c$. According to the

definition of $inj$ we obtain

\begin{center}

$v_3:\;Right(Seq(Empty, Char(c)))$

\end{center}

\noindent This is the correct result, because $r_3$ needs

to use the right-hand alternative, and then $\epsilon$ needs

to match the empty string and $c$ needs to match $c$.

Next we need to inject back the letter $b$ into $v_3$. This

gives

\begin{center}

$v_2:\;Seq(Empty, Seq(Char(b), Char(c)))$

\end{center}

\noindent Finally we need to inject back the letter $a$ into

$v_2$ giving the final result

\begin{center}

$v_1:\;Seq(Char(a), Seq(Char(b), Char(c)))$

\end{center}

\noindent This now corresponds to how the regular

expression $a \cdot (b \cdot c)$ matched the string $abc$.

There are a few auxiliary functions that are of interest

in analysing this algorithm. One is called \emph{flatten},

written $|\_|$, which extracts the string ``underlying'' a 

value. It is defined recursively as

\begin{center}

\begin{tabular}{lcl}

  $|Empty|$     & $\dn$ & $[]$\\

  $|Char(c)|$   & $\dn$ & $[c]$\\

  $|Left(v)|$   & $\dn$ & $|v|$\\

  $|Right(v)|$  & $\dn$ & $|v|$\\

  $|Seq(v_1,v_2)|$& $\dn$ & $|v_1| \,@\, |v_2|$\\

  $|[v_1,\ldots ,v_n]|$ & $\dn$ & $|v_1| \,@\ldots @\, |v_n|$\\

\end{tabular}

\end{center}

\noindent Using flatten we can see what is the string behind 

the values calculated by $mkeps$ and $inj$ in our running 

example are:

\begin{center}

\begin{tabular}{ll}

$|v_4|$: & $[]$\\

$|v_3|$: & $c$\\

$|v_2|$: & $bc$\\

$|v_1|$: & $abc$

\end{tabular}

\end{center}

\noindent 

This indicates that $inj$ indeed is injecting, or adding, back

a character into the value.

\subsubsection*{Simplification}

Generally the matching algorithms based on derivatives do

poorly unless the regular expressions are simplified after

each derivatives step. But this is a bit more involved in 

algorithm of Sulzmann \& Lu. Consider the last derivation

step in our running example

\begin{center}

\end{center}

This requires what I call \emph{rectification functions}. They

need to be calculated whenever a regular expression gets

simplified. Rectification functions take a value as argument

and return a (rectified) value. Our simplification rules so

far are

\begin{center}

\begin{tabular}{l@{\hspace{2mm}}c@{\hspace{2mm}}l}

$r \cdot \varnothing$ & $\mapsto$ & $\varnothing$\\ 

$\varnothing \cdot r$ & $\mapsto$ & $\varnothing$\\ 

$r \cdot \epsilon$ & $\mapsto$ & $r$\\ 

$\epsilon \cdot r$ & $\mapsto$ & $r$\\ 

$r + \varnothing$ & $\mapsto$ & $r$\\ 

$\varnothing + r$ & $\mapsto$ & $r$\\ 

$r + r$ & $\mapsto$ & $r$\\ 

\end{tabular}

\end{center}

\noindent Applying them to $r_4$ will require several nested

\subsubsection*{Records and Tokenisation}

\newpage

Algorithm by Sulzmann, Lexing

\end{document}

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