Autospearman: Automatically mitigating correlated software metrics for interpreting defect models
The interpretation of defect models heavily relies on software metrics that are used to construct them. However, such software metrics are often correlated in defect models. Prior work often uses feature selection techniques to remove correlated metrics in order to improve the performance of defect...
Saved in:
Main Authors: | JIARPAKDEE, Jirayus, TANTITHAMTHAVORN, Chakkrit, TREUDE, Christoph |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2018
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/8829 https://ink.library.smu.edu.sg/context/sis_research/article/9832/viewcontent/icsme18a.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Artefact: An R implementation of the autospearman function
by: JIARPAKDEE, Jirayus, et al.
Published: (2018) -
The impact of automated feature selection techniques on the interpretation of defect models
by: JIARPAKDEE, Jirayus, et al.
Published: (2020) -
Evaluating Defect Prediction using a Massive Set of Metrics
by: XUAN, Xiao, et al.
Published: (2015) -
A comparison between software design and code metrics for the prediction of software fault content
by: Zhao, M., et al.
Published: (2014) -
F-metric: A WWW-based framework for intelligent formulation and analysis of metric queries
by: Chee, C.-L., et al.
Published: (2014)