Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: An Improved SDA Based Defect Prediction Framework for Both Within-Project and Cross-Project Class-Imbalance Problems
Using Class Imbalance Learning for Software Defect Prediction
Studying just-in-time defect prediction using cross-project models
Cross-project defect prediction using a connectivity-based unsupervised classifier
Online defect prediction for imbalanced data
Defect Prediction: Accomplishments and Future Challenges
Better cross company defect prediction
Balancing the trade-off between accuracy and interpretability in software defect prediction
Effort-aware just-in-time defect prediction: simple unsupervised models could be better than supervised models
Combining Particle Swarm Optimization based Feature Selection and Bagging Technique for Software Defect Prediction
An empirical study of just-in-time defect prediction using cross-project models
Automated parameter optimization of classification techniques for defect prediction models
HYDRA: Massively Compositional Model for Cross-Project Defect Prediction
Automatically learning semantic features for defect prediction
On the Class Imbalance Problem
Revisiting unsupervised learning for defect prediction
Software defect association mining and defect correction effort prediction
Sampling imbalance dataset for software defect prediction using hybrid neuro-fuzzy systems with Naive Bayes classifier
Metaheuristic Optimization based Feature Selection for Software Defect Prediction
Towards identifying software project clusters with regard to defect prediction
Empirical assessment of machine learning based software defect prediction techniques
An Extended Fixed Priority Scheme for Mixed Criticality Systems
Correcting sample selection bias by unlabeled data
Developing and validating an instrument for measuring user-perceived web quality
Spline Fusion: A continuous-time representation for visual-inertial fusion with application to rolling shutter cameras.
Relationship between internet use and depression: Focus on physiological mood oscillations, social networking and online addictive behavior