more results added to paper

diff --git a/a4/Makefile b/a4/Makefile
index 418142e..e20addd 100644 (file)
--- a/a4/Makefile
+++ b/a4/Makefile
@@ -1,7 +1,11 @@
 LATEX:=latex
 
 DOCUMENT:=tt4
-MODELS=model.small.LStar.rand.eps model.partial.LStar.rand.eps model.full.LStar.rand.eps
+MODELS=model.small.LStar.rand.eps model.small.TTT.rand.eps model.small.RS.rand.eps model.small.KV.rand.eps \
+       model.small.LStar.wm.eps model.small.TTT.wm.eps model.small.RS.wm.eps model.small.KV.wm.eps \
+       model.partial.LStar.rand.eps model.partial.TTT.rand.eps model.partial.RS.rand.eps model.partial.KV.rand.eps \
+       model.partial.LStar.wm.eps model.partial.TTT.wm.eps model.partial.RS.wm.eps model.partial.KV.wm.eps \
+       model.partial.LStar.rand.eps model.full.LStar.rand.eps
 
 .SECONDARY: $(DOCUMENT).fmt
 .PHONY: clean

diff --git a/a4/preamble.tex b/a4/preamble.tex
index a3a539e..7e1f18f 100644 (file)
--- a/a4/preamble.tex
+++ b/a4/preamble.tex
@@ -4,6 +4,7 @@
 \usepackage[dvipdfm]{hyperref}
 \usepackage{graphicx}
 \usepackage{longtable}
+\usepackage{float}
 
 \author{%
        Charlie Gerhardus\and

diff --git a/a4/question1.tex b/a4/question1.tex
index 657d022..0370589 100644 (file)
--- a/a4/question1.tex
+++ b/a4/question1.tex
@@ -1,7 +1,7 @@
 The Candymachine was learned using LearnLib. Figure~\ref{fig:candy} shows the 
 learned model. In this Figure S0 is the initial state. 
 
-\begin{figure}
+\begin{figure}[H]
        \includegraphics[width=1.7\textwidth,natwidth=2389,natheight=891]{1candyFig.png} 
        \caption{Learned model of the candy machine}
        \label{fig:candy}

diff --git a/a4/question2.tex b/a4/question2.tex
index 8286ddb..0371752 100644 (file)
--- a/a4/question2.tex
+++ b/a4/question2.tex
@@ -15,12 +15,23 @@ We divided the input alphabet into three sets, this way we can control the size
 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
-\paragraph{Model learned with small input alphabet}\r
-\includegraphics{model.small.LStar.rand.eps}\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
-\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}
\ No newline at end of file
+\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

diff --git a/a4/question3.tex b/a4/question3.tex
index 212b38d..51dfc07 100644 (file)
--- a/a4/question3.tex
+++ b/a4/question3.tex
@@ -1,5 +1,9 @@
 The table below contains some statistics about all the different parameter configurations we ran learnlib with.\r
-All except \emph{RivestSchapire} using the Random test method result in the correct model being learned. \r
+The \emph{RivestSchapire} learner using the Random test method resulted in an incorrect model being learned.\r
+When the \emph{KearnsVazirani} learner using the WMethod tester wasn't able to learn a model, this is due the learner hitting a non-deterministic path. \r
+This problem hasn't anything to do with the actual learner and is the result of a uncaught error situation in the adapter.\r
+This shows us that a leaner can be used to test software, since we discovered a bug in our adapter.\r
+Due to time constrains we were not able to fix this bug.\r
 When \emph{WMethod} is selected as the testing method \emph{RivestSchapire} is also able to learn the correct model.\r
 \emph{WMethod} does however increase the time needed to learn the model significantly, when a different learner is used there is no reason not to use the Random testing method.\r
 \r

diff --git a/a4/tt4.tex b/a4/tt4.tex
index 7461b89..a9ec7f3 100644 (file)
--- a/a4/tt4.tex
+++ b/a4/tt4.tex
@@ -16,6 +16,10 @@
 \section{Question 4}
 \input{question4.tex}
 
+\appendix
+\section{Models}
+\input{models.tex}
+
 \nocite{*}
 \bibliographystyle{ieeetr}
 \bibliography{tt4}