Hao Wang

Peking University

Haidian District, Beijing, China

My formal name is Hao, but I usually go by Tony. I am a junior undergraduate student in Peking University, China. I study computer science in Turing class. I am interested in programming languages, formal methods, and software engineering. I am also interested in quantum algorithms, and optimization problems.

I am very fortunate to be advised by Prof. Darko Marinov, Prof. Tao Xie, and Prof. Tongyang Li. I plan to focus my undergraduate research on quantum algorithms, under the supervision of Prof. Tongyang Li.

I am fond of using vim and neovim to edit my codes. I also like to play with the syntax highlight and vimscript. I am now using a vimrc adapted from @amix3k’s. If you are curious, here is my current vimrc: Tony’s .vimrc

I also love listening to various genres of music. Recently I have become a lover of Jazz music. My favorite albums are Wynton Marsalis’ Black Code and Skyline by Ron Carter.

You can find my CV here: Tony’s Curriculum Vitae

news

Jan 17, 2024	Our paper Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss was recently accepted at ICLR’24! Looking forward to visiting Vienna in the spring!
Sep 2, 2023	I am selected as a young researcher at HLF 2023! Looking forward to meeting the laureates and peer researchers
Jun 28, 2023	During this summer I will be visiting UIUC and working on software testing!
Feb 1, 2023	Our paper BADGE: Prioritizing UI Events with Hierarchical Multi-Armed Bandits for Automated UI Testing was recently accepted at ICSE’23!
Dec 24, 2021	Our paper A Theoretical Analysis of Random Regression Test Prioritization was recently accepted at TACAS’22!

selected publications

TACAS
A Theoretical Analysis of Random Regression Test Prioritization

Yi, Pu, Wang, Hao, Xie, Tao, Marinov, Darko, and Lam, Wing

In TACAS 2022

Abs Bib

Regression testing is an important activity to check software changes by running the tests in a test suite to inform the developers whether the changes lead to test failures. Regression test prioritization (RTP) aims to inform the developers faster by ordering the test suite so that tests likely to fail are run earlier. Many RTP techniques have been proposed and are often compared with the random RTP baseline by sampling some of the n! different test-suite orders for a test suite with n tests. However, there is no theoretical analysis of random RTP. We present such an analysis, deriving probability mass functions and expected values for metrics and scenarios commonly used in RTP research. Using our analysis, we revisit some of the most highly cited RTP papers and find that some presented results may be due to insufficient sampling. Future RTP research can leverage our analysis and need not use random sampling but can use our simple formulas or algorithms to more precisely compare with random RTP.
@inproceedings{pu2022randomrtp, author = {Yi, Pu and Wang, Hao and Xie, Tao and Marinov, Darko and Lam, Wing}, editor = {Fisman, Dana and Rosu, Grigore}, title = {A Theoretical Analysis of Random Regression Test Prioritization}, booktitle = {TACAS}, year = {2022}, publisher = {Springer International Publishing}, address = {Cham}, pages = {217--235}, isbn = {978-3-030-99527-0}, }

ICSE

BADGE: Prioritizing UI Events with Hierarchical Multi-Armed Bandits for Automated UI Testing

Ran, Dezhi, Wang, Hao, Wang, Wenyu, and Xie, Tao

In ICSE 2023

Bib

@inproceedings{dezhi2023android,
  booktitle = {ICSE},
  author = {Ran, Dezhi and Wang, Hao and Wang, Wenyu and Xie, Tao},
  title = {BADGE: Prioritizing UI Events with Hierarchical Multi-Armed Bandits for Automated UI Testing},
  year = {2023},
}