Hongmin Lu
Orcid: 0000-0002-3558-9754
According to our database1,
Hongmin Lu
authored at least 37 papers
between 2003 and 2024.
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Bibliography
2024
Sci. Comput. Program., 2024
Behavioral Modeling of Direct-Conversion Receivers for Nonlinear Distortion Mitigation.
IEEE Access, 2024
2023
Analysis on the Effect of Phase Noise on the Performance of Satellite Communication and Measurement System.
Symmetry, November, 2023
Construction and Analysis of the EMC Evaluation Model for Vehicular Communication Systems Based on Digital Maps.
Remote. Sens., October, 2023
Deriving Thresholds of Object-Oriented Metrics to Predict Defect-Proneness of Classes: A Large-Scale Meta-Analysis.
Int. J. Softw. Eng. Knowl. Eng., 2023
2022
CBUA: A Probabilistic, Predictive, and Practical Approach for Evaluating Test Suite Effectiveness.
IEEE Trans. Software Eng., 2022
IEEE Trans. Geosci. Remote. Sens., 2022
2021
How Far Have We Progressed in Identifying Self-admitted Technical Debts? A Comprehensive Empirical Study.
ACM Trans. Softw. Eng. Methodol., 2021
A Novel 4D Track-before-Detect Approach for Weak Targets Detection in Clutter Regions.
Remote. Sens., 2021
Inf. Softw. Technol., 2021
2020
Boosting crash-inducing change localization with rank-performance-based feature subset selection.
Empir. Softw. Eng., 2020
2019
CoRR, 2019
Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering, 2019
2018
How Far We Have Progressed in the Journey? An Examination of Cross-Project Defect Prediction.
ACM Trans. Softw. Eng. Methodol., 2018
2017
Understanding the value of considering client usage context in package cohesion for fault-proneness prediction.
Autom. Softw. Eng., 2017
An empirical investigation into the cost-effectiveness of test effort allocation strategies for finding faults.
Proceedings of the IEEE 24th International Conference on Software Analysis, 2017
Proceedings of the 2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, 2017
Training Data Selection for Cross-Project Defection Prediction: Which Approach Is Better?
Proceedings of the 2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, 2017
2016
An empirical investigation into the effect of slice types on slice-based cohesion metrics.
Inf. Softw. Technol., 2016
Effort-aware just-in-time defect prediction: simple unsupervised models could be better than supervised models.
Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering, 2016
2015
Are Slice-Based Cohesion Metrics Actually Useful in Effort-Aware Post-Release Fault-Proneness Prediction? An Empirical Study.
IEEE Trans. Software Eng., 2015
An empirical analysis of package-modularization metrics: Implications for software fault-proneness.
Inf. Softw. Technol., 2015
Is Learning-to-Rank Cost-Effective in Recommending Relevant Files for Bug Localization?
Proceedings of the 2015 IEEE International Conference on Software Quality, 2015
Predicting Vulnerable Components via Text Mining or Software Metrics? An Effort-Aware Perspective.
Proceedings of the 2015 IEEE International Conference on Software Quality, 2015
Proceedings of the 2015 IEEE International Conference on Software Quality, 2015
2014
Proceedings of the Eighth International Conference on Software Security and Reliability, 2014
2012
Empir. Softw. Eng., 2012
An in-depth investigation into the relationships between structural metrics and unit testability in object-oriented systems.
Sci. China Inf. Sci., 2012
2010
Proceedings of the Fifth IEEE International Symposium on Service-Oriented System Engineering, 2010
2008
Proceedings of the Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008
2005
2004
ACM SIGSOFT Softw. Eng. Notes, 2004
2003
Proceedings of the 10th Asia-Pacific Software Engineering Conference (APSEC 2003), 2003