a4/question2.tex

   1 In order to be allow learnlib to learn the TCP model it was necessary to have a deterministic model.
   2 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.
   3 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.
   4
   5 We divided the input alphabet into three sets, this way we can control the size of the model learned by learnlib.
   6
   7 \begin{longtable}{|c|l|}
   8         \caption{Different input alphabets used during learning.} \\\hline
   9         Alphabet & Inputs \\\hline \hline
  10         small & SYN, ACK \\\hline
  11         partial & SYN, ACK, DATA \\\hline
  12         full & SYN, ACK, DATA, RST, FIN \\\hline
  13 \end{longtable}
  14
  15 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.
  16 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.
  17
  18 \paragraph{Model learned with small input alphabet}
  19 \includegraphics{model.small.LStar.rand.eps}
  20
  21
  22 \paragraph{Model learned with partial input alphabet}
  23 \includegraphics{model.partial.LStar.rand.eps}
  24
  25 \paragraph{Model learned with full input alphabet}
  26 \includegraphics{model.full.LStar.rand.eps}