Some Approaches for Software Defect Prediction
Name
Hans Raukas
Abstract
The main idea of this thesis is to give a general overview of the processes within the soft-ware defect prediction models using machine learning classifiers and to provide analysis to some of the results of the evaluation experiments conducted in the research papers covered in this work. Additionally, a brief explanation of the algorithms used within the software defect prediction models covered in this work is given and some of the evaluation measures used to evaluate the prediction accuracy of software defect prediction models are listed and explained. Also, a general overview of the processes within a handful of specific software defect prediction models is provided.
Graduation Thesis language
English
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Helle Hein
Defence year
2017