My research interests include distributed systems, machine learning systems, and software dependability.
Vicious Cycles in Distributed Software Systems.
Shangshu Qian, Wen Fan, Lin Tan, and Yongle Zhang.
In the proceedings of the IEEE/ACM International Conference on Automated Software Engineering, September, 2023. Kirchberg, Luxembourg. ASE-2023 (Acceptance Rate: 21%, or 134/629) [Slides]
EAGLE: Creating Equivalent Graphs to Test Deep Learning Libraries.
Jiannan Wang, Thibaud Lutellier, Shangshu Qian, Hung Viet Pham, and Lin Tan.
In the proceedings of the 44th International Conference on Software Engineering, May 2022. Pittsburgh, USA. ICSE-2022 (Acceptance Rate: 26%, or 197/751)
Are My Deep Learning Systems Fair? An Empirical Study of Fixed-Seed Training.
Shangshu Qian, Hung Viet Pham, Thibaud Lutellier, Zeou Hu, Jungwon Kim, Lin Tan, Yaoliang Yu, Jiahao Chen, and Sameena Shah.
In the proceedings of the Advances in Neural Information Processing Systems 34, December 2021. Virtual. NeurIPS-2021 (Acceptance Rate: 26%, or 2344/9122)
Problems and Opportunities in Training Deep Learning Software Systems: An Analysis of Variance.
Hung Viet Pham, Shangshu Qian, Jiannan Wang, Thibaud Lutellier, Jonathan Rosenthal, Lin Tan, Yaoliang Yu, and Nachiappan Nagappan.
In the proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering, September 2020. Virtual/Melbourne, Australia. ASE-2020 (Acceptance Rate: 22.5%, or 93/414)
Won ACM SIGSOFT Distinguished Paper Award!