goede dingen

[tt2015.git] / a4 / question2.tex

diff --git a/a4/question2.tex b/a4/question2.tex
index 0371752..cf879c0 100644 (file)
--- a/a4/question2.tex
+++ b/a4/question2.tex
@@ -1,37 +1,52 @@
-In order to be allow learnlib to learn the TCP model it was necessary to have a deterministic model.\r
-We accomplished this by modifying the adapter so it can reach a \emph{ERROR} or \emph{CLOSED} state. In these states all inputs are discarded and a default output is returned.\r
-In the case of a state where an input results in a non-deterministic output we jump to the \emph{ERROR} state for additional this given input. When the connection is successfully closed using a \emph{FIN} packet we move the adapter to the \emph{CLOSED} state.\r
-\r
-We divided the input alphabet into three sets, this way we can control the size of the model learned by learnlib.\r
-\r
-\begin{longtable}{|c|l|}\r
-       \caption{Different input alphabets used during learning.} \\\hline\r
-       Alphabet & Inputs \\\hline \hline\r
-       small & SYN, ACK \\\hline\r
-       partial & SYN, ACK, DATA \\\hline\r
-       full & SYN, ACK, DATA, RST, FIN \\\hline\r
-\end{longtable}\r
-\r
-Just as in our previous assignment the \emph{DATA} packet is actually a \emph{ACK} with an user data payload and the \emph{push} flag set. \r
-These input alphabets will influence the size of the model produced. \emph{small} will result in a 2 state model, \emph{partial} will be the full model without the \emph{CLOSED} state and \emph{full} should result in the full model as used in the previous assignment.\r
-\r
-\begin{figure}[H]\r
-       \centering\r
-       \includegraphics[scale=0.75]{model.small.LStar.rand.eps}\r
-       \vspace{5mm}\r
-       \caption{Model learned with small input alphabet}\r
-\end{figure}\r
-\r
-\begin{figure}[H]\r
-       \centering\r
-       \includegraphics[width=\textwidth]{model.partial.LStar.rand.eps}\r
-       \vspace{5mm}\r
-       \caption{Model learned with partial input alphabet}\r
-\end{figure}\r
-\r
-\begin{figure}[H]\r
-       \centering\r
-       \includegraphics[width=1.2\textwidth]{model.full.LStar.rand.eps}\r
-       \vspace{5mm}\r
-       \caption{Model learned with full input alphabet}\r
-\end{figure}\r
+In order to be allow learnlib to learn the TCP model it was necessary to have a
+deterministic model.  We accomplished this by modifying the adapter so it can
+reach a \texttt{ERROR} or \texttt{CLOSED} state. In these states all inputs are
+discarded and a default output is returned.  In the case of a state where an
+input results in a non-deterministic output we jump to the \texttt{ERROR} state
+for additional this given input. When the connection is successfully closed
+using a \texttt{FIN} packet we move the adapter to the \texttt{CLOSED} state.
+
+We divided the input alphabet into three sets, this way we can control the size
+of the model learned by learnlib.
+
+\begin{table}[H]
+       \begin{tabular}{cl}
+               \toprule
+               Alphabet & Inputs \\
+               \midrule
+               small & \texttt{SYN}, \texttt{ACK} \\
+               partial & \texttt{SYN}, \texttt{ACK}, \texttt{DATA} \\
+               full & \texttt{SYN}, \texttt{ACK}, \texttt{DATA}, \texttt{RST},
+                       \texttt{FIN} \\
+               \bottomrule
+       \end{tabular}
+       \caption{Different input alphabets used during learning.}
+\end{table}
+
+Just as in our previous assignment the \texttt{DATA} packet is actually a
+\texttt{ACK} with an user data payload and the \emph{push} flag set.  These
+input alphabets will influence the size of the model produced. \emph{small}
+will result in a 2 state model, \emph{partial} will be the full model without
+the \texttt{CLOSED} state and \emph{full} should result in the full model as
+used in the previous assignment.
+%
+%\begin{figure}[H]
+%      \centering
+%      \includegraphics[scale=0.75]{model.small.LStar.rand.eps}
+%      \vspace{5mm}
+%      \caption{Model learned with small input alphabet}
+%\end{figure}
+%
+%\begin{figure}[H]
+%      \centering
+%      \includegraphics[width=\textwidth]{model.partial.LStar.rand.eps}
+%      \vspace{5mm}
+%      \caption{Model learned with partial input alphabet}
+%\end{figure}
+%
+%\begin{figure}[H]
+%      \centering
+%      \includegraphics[width=1.2\textwidth]{model.full.LStar.rand.eps}
+%      \vspace{5mm}
+%      \caption{Model learned with full input alphabet}
+%\end{figure}