Anjiang Wei

Ph.D. Student

Computer Science, Stanford University

Email: anjiang<AT>stanford.edu

DBLP Google Scholar CV Misc



Short Bio

Anjiang Wei (魏安江 in Chinese) is a first-year PhD student in the Department of Computer Science at Stanford University, advised by Alex Aiken.
He did his (remote) internship at UIUC, working with Darko Marinov, Tao Xie, and Lingming Zhang.
Anjiang obtained his B.S. (summa cum laude) in Computer Science in 2021 from Turing Class, Peking University, advised by Yun (Eric) Liang.
Currently, he is organizing the weekly Software Research Lunch at Stanford.


Publications
  1. Yinlin Deng*, Chenyuan Yang*, Anjiang Wei, Lingming Zhang
    Fuzzing Deep-Learning Libraries via Automated Relational API Inference
    30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
    (ESEC/FSE 2022), pages to-appear, Singapore, Nov. 2022

  2. Size Zheng, Renze Chen, Anjiang Wei, Yicheng Jin, Qin Han, Liqiang Lu, Bingyang Wu, Xiuhong Li, Shengen Yan, Yun Liang
    AMOS: Enabling Automatic Mapping for Tensor Computations On Spatial Accelerators with Hardware Abstraction
    49th International Symposium on Computer Architecture
    (ISCA 2022), pages 874-887, New York City, NY, June 2022
    code slides

  3. Anjiang Wei, Yinlin Deng, Chenyuan Yang, Lingming Zhang
    Free Lunch for Testing: Fuzzing Deep-Learning Libraries from Open Source
    44th International Conference on Software Engineering
    (ICSE 2022), pages 995-1007, Pittsburgh, PA, May 2022
    code slides video (youtube)

  4. Anjiang Wei, Pu Yi, Zhengxi Li, Tao Xie, Darko Marinov, Wing Lam
    Preempting Flaky Tests via Non-Idempotent-Outcome Tests
    44th International Conference on Software Engineering
    (ICSE 2022), pages 1730-1742, Pittsburgh, PA, May 2022
    dataset slides video (youtube)

  5. Size Zheng, Renze Chen, Yicheng Jin, Anjiang Wei, Bingyang Wu, Xiuhong Li, Shengen Yan, Yun Liang
    NeoFlow: A Flexible Framework for Enabling Efficient Compilation for High Performance DNN Training
    IEEE Transactions on Parallel and Distributed Systems
    (TPDS 2022), 33(11), pages 3220-3232, 2022

  6. Pu Yi, Anjiang Wei, Wing Lam, Tao Xie, Darko Marinov
    Finding Polluter Tests Using Java PathFinder
    ACM SIGSOFT Software Engineering Notes
    (SEN 2021), 46(3), pages 37-41, July 2021
    (Extended paper of abstract presented at Java Pathfinder Online Day (JPF 2020), Virtual Workshop, November 2020)
    slides

  7. Peilun Zhang, Yanjie Jiang, Anjiang Wei, Victoria Stodden, Darko Marinov, August Shi
    Domain-Specific Fixes for Flaky Tests with Wrong Assumptions on Underdetermined Specifications
    43rd International Conference on Software Engineering
    (ICSE 2021), pages 50-61, Virtual Conference, May 2021
    slides video

  8. Anjiang Wei, Pu Yi, Tao Xie, Darko Marinov, Wing Lam
    Probabilistic and Systematic Coverage of Consecutive Test-Method Pairs for Detecting Order-Dependent Flaky Tests
    27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems
    (TACAS 2021), pages 270-287, Virtual Conference, Mar. 2021
    slides video

  9. Wing Lam, Stefan Winter, Anjiang Wei, Tao Xie, Darko Marinov, Jonathan Bell
    A Large-Scale Longitudinal Study of Flaky Tests
    35th ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications
    (OOPSLA 2020), pages 202:1-202:29, Virtual Conference, Nov. 2020
    slides video