2023
DOI: 10.28945/5193
|View full text |Cite
|
Sign up to set email alerts
|

Predicting Software Change-Proneness From Software Evolution Using Machine Learning Methods

Raed A Shatnawi

Abstract: Aim/Purpose: To predict the change-proneness of software from the continuous evolution using machine learning methods. To identify when software changes become statistically significant and how metrics change. Background: Software evolution is the most time-consuming activity after a software release. Understanding evolution patterns aids in understanding post-release software activities. Many methodologies have been proposed to comprehend software evolution and growth. As a result, change prediction is criti… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 43 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?