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Automatic Forward Slicing of Programs
Patrik, Nikolas ; Vojnar, Tomáš (oponent) ; Malík, Viktor (vedoucí práce)
This thesis presents designing new forward slicing solution for the DiffKemp tool. After strenuous analysis of currently implemented solution in DiffKemp for forward slicing we decided to retain current solution and extend it by few enhancements that should improve the analysis provided by DiffKemp in a quite big scope. We have implemented extensions so DiffKemp can perform analysis on fields of structured types which might represent run-time parameters and also we extended slicing criterion with the value of analyzed variable. Also we added support for slicing module kernel parameters. After implementing this solutions, we did experiments which proved that implemented solution has improved the analysis performed by DiffKemp.
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Graph Neural Networks for Document Analysis
Patrik, Nikolas ; Španěl, Michal (oponent) ; Hradiš, Michal (vedoucí práce)
In this thesis we use for graph neural networks for document analysis. In the beggining we introduce how these graph convolutional networks work and also we introduce concept which is used for their implementation. Next, we explain current solution that solves semantic labeling of text entities in scanned documents, what is also same as the goal of this thesis. In following chapter we present solution which should be used for the mentioned problem as well as another problem which is extraction of specific data using active learning. Gradually, we explain how this solution was implemented and what tools we have used. Before ending, we show our dataset, we have annotated and we meant to use for evaluation and training of our solution. In the end, we present results of this thesis, compare our model with others and also evaluate how our model was able to extract specified data using active learning.
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Automatic Forward Slicing of Programs
Patrik, Nikolas ; Vojnar, Tomáš (oponent) ; Malík, Viktor (vedoucí práce)
This thesis presents designing new forward slicing solution for the DiffKemp tool. After strenuous analysis of currently implemented solution in DiffKemp for forward slicing we decided to retain current solution and extend it by few enhancements that should improve the analysis provided by DiffKemp in a quite big scope. We have implemented extensions so DiffKemp can perform analysis on fields of structured types which might represent run-time parameters and also we extended slicing criterion with the value of analyzed variable. Also we added support for slicing module kernel parameters. After implementing this solutions, we did experiments which proved that implemented solution has improved the analysis performed by DiffKemp.
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