joshua/phd-thesis
Archived
1
Fork 0
Code Activity

Iets voor de outlook

Browse source
This commit is contained in:
Joshua Moerman 2018-12-28 09:49:49 +01:00
parent 09fb019921
commit 17dbe7f671
2 changed files with 28 additions and 2 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

27
content/introduction.tex
View file

@ -566,7 +566,32 @@ This work was presented at ICGI:
\startsection
[title=Conclusion and Outlook]
\todo{Twee wegen. Komen ze nog bij elkaar? Nut van nominale technieken.}
With the current tools for learning, it is possible to learn big state machines of black box systems.
However, a real bottleneck is conformance checking of the hypothesis.
This thesis provides background on conformance checking and also investigates a new algorithm.
These testing algorithm are as efficient as they can.
So in order to improve on this bottleneck, one possible direction is to consider \quotation{grey box testing}.
This means that we should be looking into using more information of the system during testing (and learning).
Often, we do have (parts of the) source code and we do know relationships between different inputs.
The question is how this additional information can be integrated in the learning and testing of systems.
Another path taken in this thesis is the research on nominal automata.
This was motivated by the problem of learning automata over an infinite alphabet.
So far, the results on nominal automata are mostly theoretical in nature.
Nevertheless, we show that the nominal algorithms can be implemented and that the algorithms can be run concretely on black box systems (\in{Chapter}[chap:learning-nominal-automata]).
However, the tools leave much to desired in terms of efficiency.
Some of the efficiency is tackled in \in{Chapter}[chap:ordered-nominal-sets] for a particular symmetry.
Another result is the fact that some automata can be \quotation{compressed} if they accept a certain type of language (\in{Chapter}[chap:separated-nominal-automata]).
Last, it would be interesting to marry the two paths taken in this thesis.
I am not aware of complete test suites for register automata or nominal automata.
The results on learning nominal automata in \in{Chapter}[chap:learning-nominal-automata] show that this should be possible, as an observation table should give a test suite.
However, there is an interesting twist to this problem.
The test methods from \in{Chapter}[chap:test-methods] can all account for extra states.
For nominal automata, we should be able to cope with extra states and extra registers.
It will be interesting to see how the test suite grows as these two dimensions increase.
\stopsection

3
environment.tex
View file

@ -67,7 +67,8 @@ This chapter is based on the following publication:
\startsetups LogoSetup
\setlayer[Logo]{
\framed[frame=off, width=1cm, height=1cm, background=color, backgroundcolor=gray, foregroundcolor=white]{\getmarking[chapternumber]}
\clip[width=1cm, height=1cm, hoffset=1.25cm, voffset=1.25cm]
{\scale[factor=100]{\rotate[rotation=-20, frame=off, width=1cm, height=1cm, background=color, backgroundcolor=gray, foregroundcolor=white]{\pagenumber}}}
}
\stopsetups