publications

2023

1. Modeling Programmer Attention as Scanpath Prediction

   Aakash Bansal, Chia-Yi Su, Zachary Karas, Yifan Zhang, Yu Huang, Toby Jia-Jun Li, and Collin McMillan

   In Proceedings of The 38th IEEE/ACM International Conference on Automated Software Engineering - New Ideas and Emerging Research Track, 2023

   Bib Code

   @inproceedings{bansal2023scanpath,
     author = {Bansal, Aakash and Su, Chia-Yi and Karas, Zachary and Zhang, Yifan and Huang, Yu and Li, Toby Jia-Jun and McMillan, Collin},
     title = {Modeling Programmer Attention as Scanpath Prediction},
     booktitle = {Proceedings of The 38th IEEE/ACM International Conference on Automated Software Engineering - New Ideas and Emerging Research Track},
     year = {2023},
   }

2. A Language Model of Java Methods with Train/Test Deduplication

   Chia-Yi Su, Aakash Bansal, Vijayanta Jain, Sepideh Ghanavati, and Collin Mcmillan

   In Proceedings of The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2023) - Tool Demonstration, 2023

   Bib Code

   @inproceedings{chia2023language,
     author = {Su, Chia-Yi and Bansal, Aakash and Jain, Vijayanta and Ghanavati, Sepideh and Mcmillan, Collin},
     title = {A Language Model of Java Methods with Train/Test Deduplication},
     booktitle = {Proceedings of The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2023) - Tool Demonstration},
     year = {2023},
   }

3. Towards modeling human attention from eye movements for neutral source code summarization

   Aakash Bansal, Bonita Sharif, and Collin McMillan

   Proceedings of ACM Human-Computer Interaction, Vol. 7, 2023

   Bib Code

   @article{bansal2023human,
     author = {Bansal, Aakash and Sharif, Bonita and McMillan, Collin},
     journal = {Proceedings of ACM Human-Computer Interaction, Vol. 7},
     year = {2023},
   }

4. An Empirical Study of Developer Behaviors for Validating and Repairing AI-Generated Code

   Ningzhi Tang, Meng Chen, Zheng Ning, Aakash Bansal, Yu Huang, Collin McMillan, and Toby Jia-Jun Li

   In Proceedings of the 13th annual workshop on the intersection of HCI and PL (PLATEAU 2023), 2023

   Bib

   @inproceedings{Tang2023,
     author = {Tang, Ningzhi and Chen, Meng and Ning, Zheng and Bansal, Aakash and Huang, Yu and McMillan, Collin and Li, Toby Jia-Jun},
     title = {{An Empirical Study of Developer Behaviors for Validating and Repairing AI-Generated Code}},
     year = {2023},
     booktitle = {Proceedings of the 13th annual workshop on the intersection of HCI and PL (PLATEAU 2023)},
     doi = {10.1184/R1/22223533.v1},
   }

5. Label Smoothing Improves Neural Source Code Summarization

   Sakib Haque, Aakash Bansal, and Collin McMillan

   In 2023 IEEE/ACM 31st International Conference on Program Comprehension (ICPC), 2023

   Bib Code

   @inproceedings{haque2023label,
     author = {Haque, Sakib and Bansal, Aakash and McMillan, Collin},
     booktitle = {2023 IEEE/ACM 31st International Conference on Program Comprehension (ICPC)},
     title = {Label Smoothing Improves Neural Source Code Summarization},
     year = {2023},
     pages = {101-112},
     doi = {10.1109/ICPC58990.2023.00025},
     publisher = {IEEE Computer Society},
   }

6. Function Call Graph Context Encoding for Neural Source Code Summarization

   Aakash Bansal, Zachary Eberhart, Zachary Karas, Yu Huang, and Collin McMillan

   IEEE Transactions on Software Engineering, 2023

   Bib Code

   @article{bansal2023callcon,
     author = {Bansal, Aakash and Eberhart, Zachary and Karas, Zachary and Huang, Yu and McMillan, Collin},
     journal = {IEEE Transactions on Software Engineering},
     title = {Function Call Graph Context Encoding for Neural Source Code Summarization},
     year = {2023},
     doi = {10.1109/TSE.2023.3279774},
   }

2022

1. A Wizard of Oz Study Simulating API Usage Dialogues With a Virtual Assistant

   Zachary Eberhart, Aakash Bansal, and Collin McMillan

   IEEE Transactions on Software Engineering, 2022

   Bib Code

   @article{eberhart2022apiza,
     author = {Eberhart, Zachary and Bansal, Aakash and McMillan, Collin},
     journal = {IEEE Transactions on Software Engineering},
     title = {A Wizard of Oz Study Simulating API Usage Dialogues With a Virtual Assistant},
     year = {2022},
     volume = {48},
     number = {6},
     pages = {1883-1904},
     doi = {10.1109/TSE.2020.3040935},
   }

2. Semantic similarity metrics for evaluating source code summarization

   Sakib Haque, Zachary Eberhart, Aakash Bansal, and Collin McMillan

   In Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension, 2022

   Bib Code

   @inproceedings{haque2022semantic,
     author = {Haque, Sakib and Eberhart, Zachary and Bansal, Aakash and McMillan, Collin},
     booktitle = {Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension},
     pages = {36--47},
     year = {2022},
   }

2021

1. Project-level encoding for neural source code summarization of subroutines [Distinguished Paper Award]

   Aakash Bansal, Sakib Haque, and Collin McMillan

   In 2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC), 2021

   Bib Code

   @inproceedings{bansal2021project,
     author = {Bansal, Aakash and Haque, Sakib and McMillan, Collin},
     booktitle = {2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)},
     pages = {253--264},
     year = {2021},
     organization = {IEEE},
     award = {IEEE/ACM Distinguished Paper Award}
   }

2. Ensemble Models for Neural Source Code Summarization of Subroutines

   Alexander LeClair, Aakash Bansal, and Collin McMillan

   In 2021 IEEE International Conference on Software Maintenance and Evolution (ICSME), 2021

   Bib Code

   @inproceedings{leclair2021ensembles,
     author = {LeClair, Alexander and Bansal, Aakash and McMillan, Collin},
     booktitle = {2021 IEEE International Conference on Software Maintenance and Evolution (ICSME)},
     title = {Ensemble Models for Neural Source Code Summarization of Subroutines},
     year = {2021},
     pages = {286-297},
     doi = {10.1109/ICSME52107.2021.00032},
   }

3. A Neural Question Answering System for Basic Questions about Subroutines

   Aakash Bansal, Zachary Eberhart, Lingfei Wu, and Collin McMillan

   In 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), 2021

   Bib Code

   @inproceedings{bansal2021neural,
     author = {Bansal, Aakash and Eberhart, Zachary and Wu, Lingfei and McMillan, Collin},
     booktitle = {2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)},
     title = {A Neural Question Answering System for Basic Questions about Subroutines},
     year = {2021},
     pages = {60-71},
     doi = {10.1109/SANER50967.2021.00015},
   }

4. Action word prediction for neural source code summarization

   Sakib Haque, Aakash Bansal, Lingfei Wu, and Collin McMillan

   In 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), 2021

   Bib Code

   @inproceedings{haque2021action,
     author = {Haque, Sakib and Bansal, Aakash and Wu, Lingfei and McMillan, Collin},
     booktitle = {2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)},
     pages = {330--341},
     year = {2021},
     organization = {IEEE},
   }