Moving from Ad-hoc to a Structured Testing Approach in a Graph Analysis and Community Detection Framework

September 6th, 2023

Thesis Type
  • Master
Beka Zhvania
Submitted in
Proposal on
15/08/2023 10:00 am
Proposal room
Seminar room I5 6202
Presentation on
05/03/2024 11:15 am
Presentation room
Seminar room I5 6202
Stefan Decker
Alexander Neumann
Maximilian Kißgen

(Social) Network Analysis is investigating (social) structures of real-world networks. Networks are composed of nodes and links. Communities are sub-networks whose nodes have more links to nodes within the sub-network than to nodes outside the sub-network. Overlapping Community Detection (OCD) is the problem of identifying nodes in networks that belong to more than one sub-network. The overlapping community detection problem has an enormous importance for different fields of science like biology, neurology, sociology, media science, politics, economics, and computer science. The open source graph analysis framework WebOCD offers a large collection of OCD algorithms but the number of contributions to the project have left WebOCD without a clear approach to testing besides the use of the jUnit framework.
The goal of this thesis is to streamline testing in WebOCD and to achieve coverage comparable to other sate-of-the-art open source projects. With the use of generative AI, the thesis also aims to produce test cases in a semi-automated fashion.

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