goede dingen

[tt2015.git] / a4 / question2.tex

diff --git a/a4/question2.tex b/a4/question2.tex
index 2e098c1..cf879c0 100644 (file)
--- a/a4/question2.tex
+++ b/a4/question2.tex
@@ -1,40 +1,52 @@
-In order to be allow learnlib to learn the TCP model it was necessary to have a\r
-deterministic model.  We accomplished this by modifying the adapter so it can\r
-reach a \texttt{ERROR} or \texttt{CLOSED} state. In these states all inputs are\r
-discarded and a default output is returned.  In the case of a state where an\r
-input results in a non-deterministic output we jump to the \texttt{ERROR} state\r
-for additional this given input. When the connection is successfully closed\r
-using a \texttt{FIN} packet we move the adapter to the \texttt{CLOSED} state.\r
-\r
-We divided the input alphabet into three sets, this way we can control the size\r
-of the model learned by learnlib.\r
-\r
-\begin{table}[H]\r
-       \begin{tabular}{cl}\r
-               \toprule\r
-               Alphabet & Inputs \\\r
-               \midrule\r
-               small & \texttt{SYN}, \texttt{ACK} \\\r
-               partial & \texttt{SYN}, \texttt{ACK}, \texttt{DATA} \\\r
-               full & \texttt{SYN}, \texttt{ACK}, \texttt{DATA}, \texttt{RST},\r
-                       \texttt{FIN} \\\r
-               \bottomrule\r
-       \end{tabular}\r
-       \caption{Different input alphabets used during learning.}\r
-\end{table}\r
-\r
-Just as in our previous assignment the \texttt{DATA} packet is actually a\r
-\texttt{ACK} with an user data payload and the \emph{push} flag set.  These\r
-input alphabets will influence the size of the model produced. \emph{small}\r
-will result in a 2 state model, \emph{partial} will be the full model without\r
-the \texttt{CLOSED} state and \emph{full} should result in the full model as\r
-used in the previous assignment.\r
-\r
-\paragraph{Model learned with small input alphabet}\r
-%\includegraphics{model.small.LStar.rand.eps}\r
-\r
-\paragraph{Model learned with partial input alphabet}\r
-%\includegraphics{model.partial.LStar.rand.eps}\r
-\r
-\paragraph{Model learned with full input alphabet}\r
-%\includegraphics{model.full.LStar.rand.eps}\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}