79 lines
2.6 KiB
TeX
79 lines
2.6 KiB
TeX
\definepapersize[stellingen][width=160mm, height=230mm]
|
|
\setuppapersize[stellingen]
|
|
\mainlanguage[nl]
|
|
|
|
%\showframe
|
|
\setuplayout
|
|
[width=middle,
|
|
height=middle,
|
|
header=0mm,
|
|
footer=0mm]
|
|
\setuppagenumbering[state=stop, alternative=singlesided]
|
|
|
|
\definefontfeature[default][default][expansion=quality,protrusion=quality,onum=yes,kern=yes,liga=yes]
|
|
\setupalign[hz,hanging]
|
|
\setupcolors[state=stop]
|
|
|
|
\definefontfamily[mainfamily] [rm] [TeX Gyre Pagella]
|
|
\definefontfamily[mainfamily] [mm] [Neo Euler] [rscale=0.95]
|
|
\definefontfamily[mainfamily] [tt] [Latin Modern Mono][rscale=1.03]
|
|
\setupbodyfont[mainfamily,11pt]
|
|
|
|
\setuphead[chapter][sectionsegments=chapter, command=\MyChapter, header=empty]
|
|
\define[2]\MyChapter{\midaligned{#2}}
|
|
|
|
\setupindenting[no]
|
|
\setupwhitespace[big]
|
|
|
|
|
|
\starttext
|
|
|
|
\startchapter
|
|
[title={Stellingen}]
|
|
|
|
\startalignment[center]
|
|
Behorend bij het proefschrift \quotation{\en Nominal Techniques and Black \break Box Testing for Automata Learning\nl} van Joshua Moerman
|
|
\stopalignment
|
|
|
|
\mainlanguage[en]
|
|
\startitemize[n]
|
|
\item
|
|
Bisimulations are not only useful for comparing white box systems.
|
|
They can also be used in black box testing for proving completeness of test suites.
|
|
By using bisimuations, we obtain simple and general proofs.
|
|
|
|
\item
|
|
It is well possible to learn a big, industrial piece of software using active automata learning.
|
|
A remaining bottleneck is how to find counterexamples.
|
|
|
|
\item
|
|
All the ingredients for a test generation methods such as W-method can be constructed in $\mathcal{O}(n \log n)$ time for state machines of size $n$.
|
|
From these ingredients, the test suite can be directly enumerated.
|
|
|
|
\item
|
|
Nominal sets provide good semantics for register automata.
|
|
From these semantics we see that the {\tt L}$^{\ast}$ algorithm seamlessly generalises to register automata.
|
|
|
|
\item
|
|
When computing with nominal sets, enumeration can outperform solvers, especially in situation with few variables.
|
|
|
|
\item
|
|
By restricting the expressiveness of an automaton model, we can obtain smaller automata and hence learn them more efficiently.
|
|
For example, data structures can be modelled as register automata which only read fresh values.
|
|
|
|
\item
|
|
A finite state machine is defined as a $5\frac{4}{5}$-tuple (study of several papers in FSM-based testing literature).
|
|
|
|
\item
|
|
Adjunctions don't lift themselves.
|
|
|
|
\item
|
|
Although people often think that testing is not a formal method, testing of finite state machines can be done in a sound and complete manner.
|
|
|
|
\item
|
|
Big data is a solved problem.
|
|
A much more relevant and much harder problem is that of learning from small data.
|
|
|
|
\stopitemize
|
|
\stopchapter
|
|
\stoptext
|