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Journal Articles
- 2024
[j4]Yifan Zhang
, Jiliang Li, Zachary Karas, Aakash Bansal, Toby Jia-Jun Li, Collin McMillan, Kevin Leach, Yu Huang:
EyeTrans: Merging Human and Machine Attention for Neural Code Summarization. Proc. ACM Softw. Eng. 1(FSE): 115-136 (2024)- 2023
- [j3]Aakash Bansal, Bonita Sharif, Collin McMillan:
Towards Modeling Human Attention from Eye Movements for Neural Source Code Summarization. Proc. ACM Hum. Comput. Interact. 7(ETRA): 1-19 (2023) - [j2]Aakash Bansal, Zachary Eberhart, Zachary Karas, Yu Huang, Collin McMillan:
Function Call Graph Context Encoding for Neural Source Code Summarization. IEEE Trans. Software Eng. 49(9): 4268-4281 (2023) - 2022
- [j1]Zachary Eberhart, Aakash Bansal, Collin McMillan:
A Wizard of Oz Study Simulating API Usage Dialogues With a Virtual Assistant. IEEE Trans. Software Eng. 48(6): 1883-1904 (2022)
Conference and Workshop Papers
- 2024
- [c10]Ningzhi Tang, Junwen An, Meng Chen, Aakash Bansal, Yu Huang, Collin McMillan, Toby Jia-Jun Li:
CodeGRITS: A Research Toolkit for Developer Behavior and Eye Tracking in IDE. ICSE Companion 2024: 119-123 - [c9]Ningzhi Tang, Meng Chen, Zheng Ning, Aakash Bansal, Yu Huang, Collin McMillan, Toby Jia-Jun Li:
Developer Behaviors in Validating and Repairing LLM-Generated Code Using IDE and Eye Tracking. VL/HCC 2024: 40-46 - 2023
- [c8]Sakib Haque, Aakash Bansal, Collin McMillan:
Label Smoothing Improves Neural Source Code Summarization. ICPC 2023: 101-112 - [c7]Aakash Bansal, Chia-Yi Su, Zachary Karas, Yifan Zhang, Yu Huang, Toby Jia-Jun Li, Collin McMillan:
Modeling Programmer Attention as Scanpath Prediction. ASE 2023: 1732-1736 - [c6]Chia-Yi Su, Aakash Bansal, Vijayanta Jain, Sepideh Ghanavati, Collin McMillan:
A Language Model of Java Methods with Train/Test Deduplication. ESEC/SIGSOFT FSE 2023: 2152-2156 - 2022
- [c5]Sakib Haque, Zachary Eberhart, Aakash Bansal, Collin McMillan:
Semantic similarity metrics for evaluating source code summarization. ICPC 2022: 36-47 - 2021
- [c4]Alexander LeClair, Aakash Bansal, Collin McMillan:
Ensemble Models for Neural Source Code Summarization of Subroutines. ICSME 2021: 286-297 - [c3]Aakash Bansal, Sakib Haque, Collin McMillan:
Project-Level Encoding for Neural Source Code Summarization of Subroutines. ICPC 2021: 253-264 - [c2]Aakash Bansal, Zachary Eberhart, Lingfei Wu, Collin McMillan:
A Neural Question Answering System for Basic Questions about Subroutines. SANER 2021: 60-71 - [c1]Sakib Haque, Aakash Bansal, Lingfei Wu, Collin McMillan:
Action Word Prediction for Neural Source Code Summarization. SANER 2021: 330-341
Informal and Other Publications
- 2024
- [i17]Yifan Zhang, Jiliang Li, Zachary Karas, Aakash Bansal, Toby Jia-Jun Li, Collin McMillan, Kevin Leach, Yu Huang:
EyeTrans: Merging Human and Machine Attention for Neural Code Summarization. CoRR abs/2402.14096 (2024) - [i16]Ningzhi Tang, Meng Chen, Zheng Ning, Aakash Bansal, Yu Huang, Collin McMillan, Toby Jia-Jun Li:
A Study on Developer Behaviors for Validating and Repairing LLM-Generated Code Using Eye Tracking and IDE Actions. CoRR abs/2405.16081 (2024) - [i15]Aakash Bansal, Robert Wallace, Zachary Karas, Ningzhi Tang, Yu Huang, Toby Jia-Jun Li, Collin McMillan:
Programmer Visual Attention During Context-Aware Code Summarization. CoRR abs/2405.18573 (2024) - [i14]Chia-Yi Su, Aakash Bansal, Yu Huang, Toby Jia-Jun Li, Collin McMillan:
Context-aware Code Summary Generation. CoRR abs/2408.09006 (2024) - 2023
- [i13]Sakib Haque, Aakash Bansal, Collin McMillan:
Label Smoothing Improves Neural Source Code Summarization. CoRR abs/2303.16178 (2023) - [i12]Chia-Yi Su, Aakash Bansal, Vijayanta Jain, Sepideh Ghanavati, Collin McMillan:
A Language Model of Java Methods with Train/Test Deduplication. CoRR abs/2305.08286 (2023) - [i11]Aakash Bansal, Bonita Sharif, Collin McMillan:
Towards Modeling Human Attention from Eye Movements for Neural Source Code Summarization. CoRR abs/2305.09773 (2023) - [i10]Aakash Bansal, Siyuan Jiang, Sakib Haque, Collin McMillan:
Statement-based Memory for Neural Source Code Summarization. CoRR abs/2307.11709 (2023) - [i9]Aakash Bansal, Chia-Yi Su, Zachary Karas, Yifan Zhang, Yu Huang, Toby Jia-Jun Li, Collin McMillan:
Modeling Programmer Attention as Scanpath Prediction. CoRR abs/2308.13920 (2023) - [i8]Aakash Bansal, Chia-Yi Su, Collin McMillan:
Revisiting File Context for Source Code Summarization. CoRR abs/2309.02326 (2023) - 2022
- [i7]Sakib Haque, Zachary Eberhart, Aakash Bansal, Collin McMillan:
Semantic Similarity Metrics for Evaluating Source Code Summarization. CoRR abs/2204.01632 (2022) - 2021
- [i6]Sakib Haque, Aakash Bansal, Lingfei Wu, Collin McMillan:
Action Word Prediction for Neural Source Code Summarization. CoRR abs/2101.02742 (2021) - [i5]Aakash Bansal, Zachary Eberhart, Lingfei Wu, Collin McMillan:
A Neural Question Answering System for Basic Questions about Subroutines. CoRR abs/2101.03999 (2021) - [i4]Aakash Bansal, Sakib Haque, Collin McMillan:
Project-Level Encoding for Neural Source Code Summarization of Subroutines. CoRR abs/2103.11599 (2021) - [i3]Zachary Eberhart, Aakash Bansal, Collin McMillan:
A Wizard of Oz Study Simulating API Usage Dialogues with a Virtual Assistant. CoRR abs/2106.12645 (2021) - [i2]Alexander LeClair, Aakash Bansal, Collin McMillan:
Ensemble Models for Neural Source Code Summarization of Subroutines. CoRR abs/2107.11423 (2021) - 2020
- [i1]Zachary Eberhart, Aakash Bansal, Collin McMillan:
The Apiza Corpus: API Usage Dialogues with a Simulated Virtual Assistant. CoRR abs/2001.09925 (2020)
Coauthor Index
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