Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs | Paper Citation Record

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This paper cites In2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER).

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)

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This paper cites InProceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation, Dekai Wu, Marine Carpuat, Xavier Carreras, and Eva Maria Vecchi (Eds.).

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation, Dekai Wu, Marine Carpuat, Xavier Carreras, and Eva Maria Vecchi (Eds.)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs https://doi.org/10

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of the 30th International Conference on Neural Information Processing Systems (Barcelona, Spain)(NIPS’16)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Engg.18, 2 (apr 2013), 277–309

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This paper cites InFindings of the Association for Computational Linguistics: EMNLP 2020, Trevor Cohn, Yulan He, and Yang Liu (Eds.).

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InFindings of the Association for Computational Linguistics: EMNLP 2020, Trevor Cohn, Yulan He, and Yang Liu (Eds.)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs GraphCodeBERT: Pre-training Code Representations with Data Flow

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This paper cites InProceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis (Santa Barbara, CA, USA)(ISSTA 2017).

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis (Santa Barbara, CA, USA)(ISSTA 2017)

Reference 24

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Unresolved cited work

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Empirical Software Engineering27, 6 (2022),

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Empirical Software Engineering21 (04 2015)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In2013 10th Working Conference on Mining Software Repositories (MSR)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs https://doi.org/10.1016/j.jss.2019.110441 Proc

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs https://doi.org/10.1007/s10664-012-9233-9 Huzefa Kagdi, Malcom Gethers, Denys Poshyvanyk, and Michael L

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In2010 17th Working Conference on Reverse Engineering

Reference 34

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This paper cites InProceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Alessandro Moschitti, Bo Pang, and Walter Daelemans (Eds.).

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Alessandro Moschitti, Bo Pang, and Walter Daelemans (Eds.)

Reference 35

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings

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This paper cites In Proceedings of the 22nd International Conference on Program Comprehension(Hyderabad, India)(ICPC 2014).

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In Proceedings of the 22nd International Conference on Program Comprehension(Hyderabad, India)(ICPC 2014)

Reference 37

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In 2016 23rd Asia-Pacific Software Engineering Conference (APSEC)

Reference 38

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering(Vasteras, Sweden)(ASE ’14)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs https://doi.org/10.1109/ICSM.2012.6405270 Quoc V

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Distributed Representations of Sentences and Documents

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Software Testing, Verification and Reliability23 (12 2013)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9,

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Efficient Estimation of Word Representations in Vector Space

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs https: //doi.org/10.1007/s10664-020-09823-w Hoan Anh Nguyen, Anh Tuan Nguyen, and Tien N

Reference 46

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In2013 IEEE 24th International Symposium on Software Reliability Engineering (ISSRE)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In2008 1st International Conference on Software Testing, Verification, and Validation

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs https://doi.org/10.1109/TSE.2010.81 Jeffrey Svajlenko, Judith F

Reference 51

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In2014 IEEE International Conference on Software Maintenance and Evolution

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering(Cary, North Carolina)(FSE ’12)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement(Bolzano-Bozen, Italy)(ESEM ’10)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs https://proceedings.neurips.cc/paper_files/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf Min Wang, Zeqi Lin, Yanzhen Zou, and Bing Xie

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)

Reference 56

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Nonlinear states and dynamics in a synthetic frequency dimension

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Logic Gates based on Interaction of Counterpropagating Light in Microresonators

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In12th Asia-Pacific Software Engineering Conference (APSEC’05)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In2006 22nd IEEE International Conference on Software Maintenance

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of the 8th ACM SIGPLAN-SIGSOFT Workshop on Program Analysis for Software Tools and Engineering(Atlanta, Georgia)(PASTE ’08)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs https://doi.org/10.1007/s10664-008- 9088-2 Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In2010 IEEE International Conference on Software Maintenance

Reference 2010

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of the 33rd International Conference on Software Engineering(Waikiki, Honolulu, HI, USA) (ICSE ’11)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In2012 34th International Conference on Software Engineering (ICSE)

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In2013 IEEE International Conference on Software Maintenance

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs https://doi.org/10.1016/j.jss.2015.02.018 Haipeng Cai, Raul Santelices, and Siyuan Jiang

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs In Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering(Singapore, Singapore) (ASE ’16)

Reference 2016

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs https://doi.org/10.1109/TSE.2016.2620458 Ben Breech, Anthony Danalis, Stacey Shindo, and Lori Pollock

Reference 2017

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Observation 9903a37d-84c9-4ece-9a0a-d28b353a6c01 · outbound

This paper cites SynCoBERT: Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation.

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs SynCoBERT: Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-07-31T23:43:45.927675Z

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Observation ee103bdb-d714-4671-b033-5fc1761370e4 · outbound

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Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Unresolved cited work

Reference 2019

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Observation f831cdd1-50c8-4f86-8956-2f21bb8fc13b · outbound

This paper cites InProceedings of the 34th International Conference on Neural Information Processing Systems(Vancouver, BC, Canada)(NIPS’20).

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of the 34th International Conference on Neural Information Processing Systems(Vancouver, BC, Canada)(NIPS’20)

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-07-31T23:43:40.736475Z

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Observation e2e8ee85-3146-49fa-8fa1-86ef30cafbac · outbound

This paper cites InProceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-07-31T23:43:40.100392Z

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Observation dca7d408-04fd-4451-8309-ea3281fdebf9 · outbound

This paper cites InProceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.).

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs InProceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.)

Reference 2022

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Observation 49216677-0b17-4b00-861c-5f233facd3b2 · outbound

This paper cites an unresolved cited work.

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs Unresolved cited work

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-07-31T23:43:41.514011Z

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Observation 34db4204-1c7b-4d75-a55e-903be2fece36 · outbound

This paper cites https://doi.org/ 10.5281/zenodo.21569282.

Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs https://doi.org/ 10.5281/zenodo.21569282

Reference 2026

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