Application of graph neural networks on software modeling
tarafından
 
Leblebici, Onur Yusuf, author.

Başlık
Application of graph neural networks on software modeling

Yazar
Leblebici, Onur Yusuf, author.

Yazar Ek Girişi
Leblebici, Onur Yusuf, author.

Fiziksel Tanımlama
x, 84 leaves: charts;+ 1 computer laser optical disc.

Özet
Deficiencies and inconsistencies introduced during the modeling of software systems can cause undesirable consequences that may result in high costs and negatively affect the quality of all developments made using these models. Therefore, creating better models will help the software engineers to build better software systems that meet expectations. One of the software modelling methods used for analysis of graphical user interfaces is Event Sequence Graphs (ESG). The goal of this thesis is to propose a method that predicts missing or forgotten links between events defined in an ESG via Graph Neural Networks (GNN). A five-step process consisting of the following steps is proposed: (i) data collection from ESG model, (ii) dataset transformation, (iii) GNN model training, (iv) validation of trained model and (v) testing the model on unseen data. Three performance metrics, namely cross entropy loss, area under curve and accuracy, were used to measure the performance of the GNN models. Examining the results of the experiments performed on different datasets and different variations of GNN, shows that even with relatively small datasets prepared from ESG models, predicts missing or forgotten links between events defined in an ESG can be achieved.

Konu Başlığı
Neural networks (Computer science)
 
Computer software.

Yazar Ek Girişi
Tuğlular, Tuğkan,
 
Belli, Fevzi,

Tüzel Kişi Ek Girişi
İzmir Institute of Technology. Computer Engineering.

Tek Biçim Eser Adı
Thesis (Master)--İzmir Institute of Technology: Computer Engineering.
 
İzmir Institute of Technology: Computer Engineering--Thesis (Master).

Elektronik Erişim
Access to Electronic Versiyon.


LibraryMateryal TürüDemirbaş NumarasıYer NumarasıDurumu/İade Tarihi
IYTE LibraryTezT002260QA76.87 .L445 2020Tez Koleksiyonu