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6 changed files with 79 additions and 5 deletions
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stellingen.tex
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stellingen.tex
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\definepapersize[stellingen][width=160mm, height=230mm]
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\setuppapersize[stellingen]
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\mainlanguage[nl]
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%\showframe
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\setuplayout
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[width=middle,
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height=middle,
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header=0mm,
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footer=0mm]
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\setuppagenumbering[state=stop, alternative=singlesided]
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\definefontfeature[default][default][expansion=quality,protrusion=quality,onum=yes,kern=yes,liga=yes]
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\setupalign[hz,hanging]
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\setupcolors[state=stop]
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\definefontfamily[mainfamily] [rm] [TeX Gyre Pagella]
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\definefontfamily[mainfamily] [mm] [Neo Euler] [rscale=0.95]
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\definefontfamily[mainfamily] [tt] [Latin Modern Mono][rscale=1.03]
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\setupbodyfont[mainfamily,11pt]
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\setuphead[chapter][sectionsegments=chapter, command=\MyChapter, header=empty]
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\define[2]\MyChapter{\midaligned{#2}}
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\setupindenting[no]
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\setupwhitespace[big]
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\starttext
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\startchapter
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[title={Stellingen}]
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\startalignment[center]
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Behorend bij het proefschrift \quotation{\en Nominal Techniques and Black \break Box Testing for Automata Learning\nl} van Joshua Moerman
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\stopalignment
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\mainlanguage[en]
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\startitemize[n]
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\item
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Bisimulations are not only useful for comparing white box systems.
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They can also be used in black box testing for proving completeness of test suites.
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By using bisimuations, we obtain simple and general proofs.
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\item
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It is well possible to learn a big, industrial piece of software using active automata learning.
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A remaining bottleneck is how to find counterexamples.
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\item
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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 $n$.
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From these ingredients, the test suite can be directly enumerated.
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\item
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Nominal sets provide good semantics for register automata.
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From these semantics we see that the {\tt L}$^{\ast}$ algorithm seamlessly generalises to register automata.
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\item
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When computing with nominal sets, enumeration can outperform solvers, especially in situation with few variables.
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\item
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By restricting the expressiveness of an automaton model, we can obtain smaller automata and hence learn them more efficiently.
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For example, data structures can be modelled as register automata which only read fresh values.
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\item
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A finite state machine is defined as a $5\frac{4}{5}$-tuple (study of several papers in FSM-based testing literature).
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\item
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Adjunctions don't lift themselves.
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\item
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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.
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\item
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Big data is a solved problem.
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A much more relevant and much harder problem is that of learning from small data.
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\stopitemize
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\stopchapter
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\stoptext
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Een FSM is een 5.65-tuple (gemiddelde over aantal referenties)
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Adjunctions don't lift themselves
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Small data
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talk/Nominal Techniques and Black Box Testing for Automata.pptm
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talk/Nominal Techniques and Black Box Testing for Automata.pptm
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talk/rect6619.png
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talk/rect6619.png
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talk/rect6619b.png
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talk/tekst.pdf
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talk/tekst.pdf
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