Colin B. Clement

According to our database1, Colin B. Clement authored at least 17 papers between 2019 and 2023.

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Bibliography

2023
Predicting Code Coverage without Execution.
CoRR, 2023

SUT: Active Defects Probing for Transcompiler Models.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Program Translation via Code Distillation.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022
Execution-based Evaluation for Data Science Code Generation Models.
CoRR, 2022

DeepPERF: A Deep Learning-Based Approach For Improving Software Performance.
CoRR, 2022

Training and Evaluating a Jupyter Notebook Data Science Assistant.
CoRR, 2022

Exploring and evaluating personalized models for code generation.
Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

DeepDev-PERF: a deep learning-based approach for improving software performance.
Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

Generating Examples from CLI Usage: Can Transformers Help?
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Learning to Reduce False Positives in Analytic Bug Detectors.
Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

2021
Distilling Transformers for Neural Cross-Domain Search.
CoRR, 2021

DeepDebug: Fixing Python Bugs Using Stack Traces, Backtranslation, and Code Skeletons.
CoRR, 2021

CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

GraphCodeBERT: Pre-training Code Representations with Data Flow.
Proceedings of the 9th International Conference on Learning Representations, 2021

Long-Range Modeling of Source Code Files with eWASH: Extended Window Access by Syntax Hierarchy.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020
PyMT5: multi-mode translation of natural language and Python code with transformers.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
On the Use of ArXiv as a Dataset.
CoRR, 2019


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