From: charlie Date: Tue, 26 Jan 2016 20:17:58 +0000 (+0100) Subject: more results added to paper X-Git-Url: https://git.martlubbers.net/?a=commitdiff_plain;h=2f64eea9a68535f4114494141d27b0d9ab9b782c;p=tt2015.git more results added to paper --- diff --git a/a4/Makefile b/a4/Makefile index 418142e..e20addd 100644 --- 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 --- 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 --- 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 --- 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. 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. -\paragraph{Model learned with small input alphabet} -\includegraphics{model.small.LStar.rand.eps} +\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} -\paragraph{Model learned with partial input alphabet} -\includegraphics{model.partial.LStar.rand.eps} - -\paragraph{Model learned with full input alphabet} -\includegraphics{model.full.LStar.rand.eps} \ No newline at end of file +\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} diff --git a/a4/question3.tex b/a4/question3.tex index 212b38d..51dfc07 100644 --- 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. -All except \emph{RivestSchapire} using the Random test method result in the correct model being learned. +The \emph{RivestSchapire} learner using the Random test method resulted in an incorrect model being learned. +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. +This problem hasn't anything to do with the actual learner and is the result of a uncaught error situation in the adapter. +This shows us that a leaner can be used to test software, since we discovered a bug in our adapter. +Due to time constrains we were not able to fix this bug. When \emph{WMethod} is selected as the testing method \emph{RivestSchapire} is also able to learn the correct model. \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. diff --git a/a4/tt4.tex b/a4/tt4.tex index 7461b89..a9ec7f3 100644 --- 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}