Predicting Bugs in Source Code. A Machine Learning Approach for Predicting Faults by utilizing Code & Change Metrics

Felder, Jodok

doi:10.34726/hss.2025.124198

Record link:

https://doi.org/10.34726/hss.2025.124198
http://hdl.handle.net/20.500.12708/213269

Title:

Predicting Bugs in Source Code. A Machine Learning Approach for Predicting Faults by utilizing Code & Change Metrics

Citation:

Felder, J. (2025). Predicting Bugs in Source Code. A Machine Learning Approach for Predicting Faults by utilizing Code & Change Metrics [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2025.124198

reposiTUm DOI:

10.34726/hss.2025.124198

CatalogPlus:

AC17467640

Publication Type:

Thesis - Diplomarbeit

Language:

English

Authors:

Felder, Jodok

Advisor:

Weippl, Edgar

Co-advisor:

Schatten, Alexander

Organisational Unit:

E194 - Institut für Information Systems Engineering

Date (published):

2025

Number of Pages:

Keywords:

Machine Learning; Bug Prediction; Code Metrics; Change Metrics; Gradient Boosting; CatBoost; Classification

Additional information:

Arbeit an der Bibliothek noch nicht eingelangt - Daten nicht geprueft - gesperrte Arbeit (bis 2026-02-24+01:00)
Abweichender Titel nach Übersetzung der Verfasserin/des Verfassers

License:

In Copyright

Appears in Collections:

Thesis

Fulltext (Version of Record (published version))

Adobe PDF

(1.27 MB)