ELBlocker: Predicting blocking bugs with ensemble imbalance learning
Context: Blocking bugs are bugs that prevent other bugs from being fixed. Previous studies show that blocking bugs take approximately two to three times longer to be fixed compared to non-blocking bugs. Objective: Thus, automatically predicting blocking bugs early on so that developers are aware of...
Saved in:
Main Authors: | XIA, Xin, David LO, SHIHAB, Emad, WANG, Xinyu, YANG, Xiaohu |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2015
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/3100 https://ink.library.smu.edu.sg/context/sis_research/article/4100/viewcontent/ELBlockerPredictingBlockingBugs_2015.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Automated bug report field reassignment and refinement prediction
by: XIA, Xin, et al.
Published: (2016) -
Automatic, high accuracy prediction of reopened bugs
by: Xia, Xin, et al.
Published: (2015) -
EFSPredictor: Predicting configuration bugs with ensemble feature selection
by: XU, Bowen, et al.
Published: (2016) -
Ensemble-Based Risk Scoring with Extreme Learning Machine for Prediction of Adverse Cardiac Events
by: Liu, Nan, et al.
Published: (2018) -
Empirical evaluation of bug linking
by: BISSYANDE, Tegawende F., et al.
Published: (2013)