-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
+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 of the model learned by learnlib.\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{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
+\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 \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
+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
+%\includegraphics{model.small.LStar.rand.eps}\r
\r
\paragraph{Model learned with partial input alphabet}\r
-\includegraphics{model.partial.LStar.rand.eps}\r
+%\includegraphics{model.partial.LStar.rand.eps}\r
\r
\paragraph{Model learned with full input alphabet}\r
-\includegraphics{model.full.LStar.rand.eps}
\ No newline at end of file
+%\includegraphics{model.full.LStar.rand.eps}\r
repositories / tt2015.git / blobdiff