Aashish Yadavally

ECSS 4.417

The University of Texas at Dallas

Richardson, TX 75082

For starters, my first name is pronounced / ɑ:ʃi:ʃ /.

I am a fifth-year Ph.D. student in Computer Science at the University of Texas at Dallas, working under the guidance of Dr. Tien N. Nguyen. My research lies at the intersection of Artificial Intelligence (AI) and Software Engineering (SE). I explore if/how machine learning models understand program behaviors, particularly focusing on partial program analysis and software security. My work has been recognized with multiple best paper awards, including the ACM SIGSOFT Distinguished Paper Award at FSE 2024, and the IEEE TCSE Distinguished Paper Award at SANER 2022.

*I am looking for tenure-track faculty positions starting Fall 2025*

Broadly, my research interests can be summarized as follows:

Large Language Models for Reasoning on Source Code (ICSE’25, FORGE’24)
Artificial Intelligence for Program Analysis (FSE’24, OOPSLA’24, ESEC/FSE’23, ICSE’23)
Artificial Intelligence for Software Security (ICSE’24, ESEC/FSE’23, ICSE’23)
Source Code Manipulation for Software Engineering Applications (ASE’22, ASE’22-NIER, SANER’22)

Throughout my academic journey, I have been fortunate to work under the guidance of/with wonderful people and researchers in:
Dr. David Shaohua Wang is an Assistant Professor in the Department of Informatics, New Jersey Institute of Technology.
Dr. Frederick Maier is the Associate Director of the Institute for Artificial Intelligence, University of Georgia.
Dr. Hemant Patil heads the Speech Research Lab, and is a Professor at the Dhirubhai Ambani Institute for Information and Communication Technology (DA-IICT).

You can find me at the following Conferences or Events
2024 OOPSLA (Pasadena, CA, USA), FSE (Porto de Galinhas, Brazil)
2023 ESEC/FSE (San Francisco, CA, USA), ICSE (Melbourne, Australia)
2022 ASE (Detroit, MI, USA), ICSE (Pittsburgh, PA, USA), SANER (Virtual)

Favourite Quotes

“The future depends on what we do in the present.” ~ Mohandas Karamchand Gandhi
“If you work with determination and with perfection, success will follow.” ~ Dhirubhai Ambani

news

Jun 23, 2024	ACM SIGSOFT Distinguished Paper Award at FSE 2024!
May 19, 2024	Will be joining Amazon as an Applied Scientist Intern for the summer!
Apr 17, 2024	Received Distinguished Reviewer Award at MSR 2024!
Mar 1, 2024	Awarded the ACM SIGSOFT CAPS Travel Grant of USD 500 to attend FSE 2024.
Feb 21, 2024	One paper accepted at FORGE 2024.
Jan 22, 2024	One paper accepted at FSE 2024.
Jan 15, 2024	Invited talk at TOOS, on Contextuality of Code Representation Learning.

selected publications

Predictive Program Slicing via Execution Knowledge-Guided Dynamic Dependence Learning

Aashish Yadavally, Yi Li, and Tien N. Nguyen

Proc. ACM Soft. Engg., 2024

🏆 ACM SIGSOFT Distinguished Paper Award

Bib PDF

@article{fse24,
  author = {Yadavally, Aashish and Li, Yi and Nguyen, Tien N.},
  title = {Predictive Program Slicing via Execution Knowledge-Guided Dynamic Dependence Learning},
  journal = {Proc. {ACM} Soft. Engg.},
  volume = {1},
  number = {{FSE}},
  pages = {271-292},
  year = {2024},
  note = {ACM SIGSOFT Distinguished Paper Award},
  award = {true}
}

A Learning-Based Approach to Static Program Slicing

Aashish Yadavally, Yi Li, Shaohua Wang, and Tien N. Nguyen

In , Apr 2024

Bib PDF

@inproceedings{oopsla24,
  author = {Yadavally, Aashish and Li, Yi and Wang, Shaohua and Nguyen, Tien N.},
  title = {A Learning-Based Approach to Static Program Slicing},
  year = {2024},
  issue_date = {April 2024},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  volume = {8},
  number = {OOPSLA1},
  journal = {Proc. ACM Program. Lang.},
  month = apr,
  articleno = {97},
  numpages = {27},
}

Commit-Level, Neural Vulnerability Detection and Assessment

Yi Li, Aashish Yadavally, Jiaxing Zhang, Shaohua Wang, and Tien N. Nguyen

In ESEC/SIGSOFT FSE, Apr 2023

Bib PDF Slides

@inproceedings{DBLP:conf/sigsoft/LiYZWN23,
  author = {Li, Yi and Yadavally, Aashish and Zhang, Jiaxing and Wang, Shaohua and Nguyen, Tien N.},
  title = {Commit-Level, Neural Vulnerability Detection and Assessment},
  booktitle = {{ESEC/SIGSOFT} {FSE}},
  pages = {1024--1036},
  publisher = {{ACM}},
  year = {2023},
}

(Partial) Program Dependence Learning

Aashish Yadavally, Tien N. Nguyen, Wenbo Wang, and Shaohua Wang

In ICSE, Apr 2023

🏆 Nominated for ACM SIGSOFT Distinguished Paper Award

Bib PDF Slides

@inproceedings{DBLP:conf/icse/YadavallyNWW23,
  author = {Yadavally, Aashish and Nguyen, Tien N. and Wang, Wenbo and Wang, Shaohua},
  title = {(Partial) Program Dependence Learning},
  booktitle = {{ICSE}},
  pages = {2501--2513},
  publisher = {{IEEE}},
  year = {2023},
  note = {ACM SIGSOFT Distinguished Paper Award},
  nomination = {true}
}

DeepVD: Toward Class-Separation Features for Neural Network Vulnerability Detection

Wenbo Wang, Tien N. Nguyen, Shaohua Wang, Yi Li, Jiyuan Zhang, and Aashish Yadavally

In ICSE, Apr 2023

Bib PDF Slides

@inproceedings{DBLP:conf/icse/WangNWLZY23,
  author = {Wang, Wenbo and Nguyen, Tien N. and Wang, Shaohua and Li, Yi and Zhang, Jiyuan and Yadavally, Aashish},
  title = {DeepVD: Toward Class-Separation Features for Neural Network Vulnerability
                    Detection},
  booktitle = {{ICSE}},
  pages = {2249--2261},
  publisher = {{IEEE}},
  year = {2023},
}

Phrase2Set: Phrase-to-Set Machine Translation and Its Software Engineering Applications

Thanh V. Nguyen, Aashish Yadavally, and Tien N. Nguyen

In SANER, Apr 2022

🏆 IEEE TCSE Distinguished Paper Award

Bib PDF

@inproceedings{DBLP:conf/wcre/NguyenYN22,
  author = {Nguyen, Thanh V. and Yadavally, Aashish and Nguyen, Tien N.},
  title = {Phrase2Set: Phrase-to-Set Machine Translation and Its Software Engineering
                    Applications},
  booktitle = {{SANER}},
  pages = {502--513},
  publisher = {{IEEE}},
  year = {2022},
  note = {IEEE TCSE Distinguished Paper Award},
  award = {true}
}