| How higher order mutant testing performs for deep learning models: A fine-grained evaluation of test effectiveness and efficiency improved from second-order mutant-classification tuples | 0 | 0.34 | 2022 |
| Mining Python fix patterns via analyzing fine-grained source code changes | 1 | 0.35 | 2022 |
| CBUA: A Probabilistic, Predictive, and Practical Approach for Evaluating Test Suite Effectiveness | 0 | 0.34 | 2022 |
| Multilevel Operation Strategy of a Vascular Interventional Robot System for Surgical Safety in Teleoperation | 1 | 0.38 | 2022 |
| PyART: Python API recommendation in real-time | 0 | 0.34 | 2021 |
| Generating Api Tags For Tutorial Fragments From Stack Overflow | 1 | 0.34 | 2021 |
| Smart Contract Development: Challenges and Opportunities | 5 | 0.47 | 2021 |
| An Empirical Study on Dynamic Typing Related Practices in Python Systems | 1 | 0.34 | 2020 |
| Clone Detection on Large Scala Codebases | 0 | 0.34 | 2020 |
| How C++ Templates Are Used for Generic Programming: An Empirical Study on 50 Open Source Systems | 0 | 0.34 | 2020 |
| Examining the effects of developer familiarity on bug fixing | 3 | 0.37 | 2020 |
| Heterogeneous Defect Prediction through Joint Metric Selection and Matching | 0 | 0.34 | 2020 |
| Multiple-boundary clustering and prioritization to promote neural network retraining | 1 | 0.37 | 2020 |
| Predictive analysis for race detection in software-defined networks. | 0 | 0.34 | 2019 |
| How Many Versions does a Bug Live in? An Empirical Study on Text Features for Bug Lifecycle Prediction. | 0 | 0.34 | 2018 |
| A study on the changes of dynamic feature code when fixing bugs: towards the benefits and costs of Python dynamic features. | 1 | 0.37 | 2018 |
| An Empirical Study of Dynamic Types for Python Projects. | 0 | 0.34 | 2018 |
| Speedoo: prioritizing performance optimization opportunities. | 2 | 0.35 | 2018 |
| Connecting software metrics across versions to predict defects | 2 | 0.35 | 2018 |
| Cost-sensitive transfer kernel canonical correlation analysis for heterogeneous defect prediction. | 8 | 0.40 | 2018 |
| Towards an understanding of change types in bug fixing code. | 5 | 0.41 | 2017 |
| How do developers fix cross-project correlated bugs?: a case study on the GitHub scientific python ecosystem. | 11 | 0.53 | 2017 |
| Software effort estimation based on open source projects: Case study of Github. | 4 | 0.42 | 2017 |
| An Empirical Study on Downstream Workarounds for Cross-Project Bugs | 2 | 0.38 | 2017 |
| An Empirical Study on the Characteristics of Python Fine-Grained Source Code Change Types | 3 | 0.37 | 2016 |
| An empirical investigation into the effect of slice types on slice-based cohesion metrics. | 1 | 0.35 | 2016 |
| Effort-aware just-in-time defect prediction: simple unsupervised models could be better than supervised models. | 41 | 0.66 | 2016 |
| Python probabilistic type inference with natural language support. | 13 | 0.56 | 2016 |
| Missing data imputation based on low-rank recovery and semi-supervised regression for software effort estimation. | 5 | 0.37 | 2016 |
| A Search Based Context-Aware Approach for Understanding and Localizing the Fault via Weighted Call Graph | 0 | 0.34 | 2016 |
| Cost-Sensitive Local Collaborative Representation for Software Defect Prediction | 0 | 0.34 | 2016 |
| Empirical analysis of network measures for predicting high severity software faults. | 2 | 0.35 | 2016 |
| Predicting Vulnerable Components via Text Mining or Software Metrics? An Effort-Aware Perspective | 7 | 0.48 | 2015 |
| Generating Test Cases for Composite Web Services by Parsing XML Documents and Solving Constraints | 1 | 0.37 | 2015 |
| Test report prioritization to assist crowdsourced testing | 27 | 0.80 | 2015 |
| An Empirical Study on C++ Concurrency Constructs | 1 | 0.35 | 2015 |
| How do developers use C++ libraries? An empirical study. | 0 | 0.34 | 2015 |
| Message from the DCPerf 2014 Workshop Organizers | 0 | 0.34 | 2015 |
| Link Prediction in Social Networks: the State-of-the-Art. | 130 | 3.02 | 2015 |
| An empirical study on the impact of Python dynamic features on change-proneness. | 1 | 0.34 | 2015 |
| The Design of the SIMPLE Programming Language | 0 | 0.34 | 2014 |
| A theoretical analysis of the risk evaluation formulas for spectrum-based fault localization | 129 | 2.72 | 2013 |
| Selecting feature subset for high dimensional data via the propositional FOIL rules | 17 | 0.93 | 2013 |
| Metamorphic slice: An application in spectrum-based fault localization | 44 | 1.21 | 2013 |
| Static Slicing for Python First-Class Objects | 5 | 0.39 | 2013 |
| Finding shrink critical section refactoring opportunities for the evolution of concurrent code in trustworthy software | 20 | 0.41 | 2013 |
| Leveraging Method Call Anomalies to Improve the Effectiveness of Spectrum-Based Fault Localization Techniques for Object-Oriented Programs | 4 | 0.39 | 2012 |
| Fault class prioritization in Boolean expressions | 3 | 0.39 | 2012 |
| Using Program Slicing To Improve The Efficiency And Effectiveness Of Cluster Test Selection | 7 | 0.44 | 2011 |
| Mutation Selection: Some Could be Better than All. | 0 | 0.34 | 2011 |
