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Title

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1		-Smart Zoom for Edge and Port Labels
	1	+A Machine Learning Approach for Node Size Approximation in Top-down Layout

Parent

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1		-Theses.Topics for Student Theses.WebHome
	1	+For Students.Topics for Student Theses.WebHome

Content

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	1	+Top-down Layout is a technique to draw large hierarchical diagrams from the root node downwards, scaling children down to fit in the space provided by their parents. This is in contrast to bottom-up layout where children are laid out first and the parents' dimensions are determined accordingly afterwards.
	2	+
	3	+In top-down layout a strategy needs to be used to set node sizes without knowledge of the hierarchical contents of the node as that has not been processed/laid out at that point. Current strategies are:
	4	+
	5	+* Using a default base size
	6	+* Counting the number of children and taking the square root as a multiplication factor for the default base size
	7	+* Computing the layout of only the children (look-ahead layout)
	8	+
	9	+The main challenge is to get an approximation that gives a suitable aspect ratio (close to what will actually be required).
	10	+
	11	+Graphs are complex feature vectors and the solution space is very large without necessarily one correct and optimal answer. Therefore, a machine learning (ML)-based approach may help find good solutions.
	12	+
	13	+== Example Top-down Layout of an SCChart ==
	14	+
	15	+[[image:attach:Controller_topdown_v3.png]]
	16	+
1	1	= Goals =
2	2
3		-* Implement a smart zoom feature for edge labels
4		-* Implement a smart zoom feature for port labels
5		-* Evaluation of sensible configurations and usability of features
	19	+* Use the KiCoDia benchmarking tool to extract feature vectors from existing models
	20	+* Train and evaluate an ML model on the extracted data sets
	21	+* Integrate the model as a new node size approximator into top-down layout
6	6
7	7	= Scope =
8	8
9		-Master's/Bachelor's Thesis
	25	+Master's (Bachelor's) Thesis
10	10
11	11	= Related Work/Literature =
12	12
13		-
	29	+[Under Review] M. Kasperowski and R. von Hanxleden, //Top-down Layout: Effectively Utilizing Zoom for Drawings of Compound Graphs//
14	14
	31	+M. Nielsen, //Neural Networks and Deep Learning//, Determination Press, 2015 ([[http:~~/~~/neuralnetworksanddeeplearning.com/index.html>>url:http://neuralnetworksanddeeplearning.com/index.html||shape="rect"]])
	32	+
	33	+I. Goodfellow and Y. Bengio and A. Courville, //Deep Learning//, MIT Press, 2016 ([[https:~~/~~/www.deeplearningbook.org/>>url:https://www.deeplearningbook.org/||shape="rect"]])
	34	+
15	15	= Involved Languages/Technologies =
16	16
17		-* Java / Xtend in SCCharts Synthesis
18		-* Typescript in klighd-vscode
	37	+* Java / Xtend, Python
	38	+* KiCo
	39	+* ML Frameworks (to be chosen)
19	19
20	20	= Supervised by =
21	21
22		-Maximilian Kasperowski
	43	+Maximilian Kasperowski in cooperation with the [[Intelligent Systems>>url:https://www.ins.informatik.uni-kiel.de/en||shape="rect"]] group.
23	23
24	24	mka@informatik.uni-kiel.de