My research lies at the unique intersection of software engineering, DL/NLP, and heterogeneous computing. The vision of my research is to democratize the development of emerging software (such as ML, heterogeneous applications, big data analytics) by reinventing software testing, debugging, program synthesis, and analysis tools. I have been selected as one of the eight MIT EECS rising stars in Systems (broadly defined) in 2021. I have received awards such as ACM SIGSOFT Research Highlights and Regents Faculty Fellowship. My research is funded by NSF, Cisco, and UCR Senate.

• SE4DA: As part of my research, we develop noval testing (ASE2020, ICSE2021) and debugging tools for Apache Spark applications.
• SE for new generation of computing: Emerging hardware, like FPGAs and quantum circuits, is shaping the future of heterogeneous computing; however, the use of such extraordinary computing power is restricted to a few software developers with microprocessor expertise. Our research aims to lower the barriers of porting traditional software to heterogeneous platforms, and making emerging hardware resources equally accessible across a diverse range of developers. This includes research over reinventing testing (FSE2021, FSE2023, ASE2021), refactoring (ICSE2020), program transformation (ASPLOS2022), and interactive programming tools.
• NLP4SE: We adapt large language models in NLP to interactive program synthesis, program summarization, and testing tools (ISSTA2024).
  
  

• Calico: Automated Knowledge Calibration and Diagnosis for Elevating AI Mastery in Code Tasks
  ISSTA'24
  
  by Yuxin Qiu, Jie Hu, Qian Zhang, Heng Yin
  Acceptance Rate: 20%
  
  The ACM SIGSOFT International Symposium on Software Testing and Analysis,
  13 pages, 2024 [slides][video][tool]
• MetaSim: A search engine for finding Similar GitHub Repositories
  ICSME'24
  
  by Md Rayhanul Masud, Md Omar Faruk Rokon, Qian Zhang, Michalis Faloutsos
  Acceptance Rate: 37%
  
  The 40th IEEE International Conference on Software Maintenance and Evolution,
  5 pages, Demonstrations, 2024
• Testing AI Systems Leveraging Graph Perturbation
  FSE'24
  
  by Zhaorui Yang, Haichao Zhu, Qian Zhang
  Acceptance Rate: 40%
  
  The ACM International Conference on the Foundations of Software Engineering, Poster, 2024
• Who is Creating Malware Repositories on GitHub and Why?
  WWW'24
  
  by Nishat Ara Tania, Md Rayhanul Masud, Md Omar Faruk Rokon, Qian Zhang, Michalis Faloutsos
  Acceptance Rate: 30%
  
  The Companion Proceedings of the ACM Web Conference 2024, 4 pages, 2024
• Augmenting Greybox Fuzzing with Generative AI
  by Jie Hu, Qian Zhang, and Heng Yin
• Leveraging Hardware Probes and Optimizations for Accelerating Fuzz Testing of Heterogeneous Applications
  ESEC/FSE'23
  
  by Jiyuan Wang, Qian Zhang, Hongbo Rong, Harry Xu, and Miryung Kim
  Acceptance Rate: 20%
  
  The 31st ACM Joint European Software Engineering Conference
  and Symposium on the Foundations of Software Engineering, 13 pages, 2023
• HeteroGen: Transpiling C to Heterogeneous HLS Code with Automated
  ASPLOS'22
  
  Test Generation and Program Repair
  Acceptance Rate: 20%
  
  by Qian Zhang, Jiyuan Wang, Harry Xu, Miryung Kim
  The 27th ACM International Conference on Architectural Support for
  Programming Languages and Operating Systems, 13 pages, 2022
• QDiff: Differential Testing of Quantum Software Stacks
  ASE'21
  
  by Jiyuan Wang, Qian Zhang, Harry Xu, Miryung Kim
  Acceptance Rate: 20%
  
  The 36th IEEE/ACM International Conference on Automated
  Software Engineering, 13 pages, 2021
• HeteroFuzz: Fuzz Testing to Detect Platform Dependent Divergence
  ESEC/FSE'21
  
  by Qian Zhang, Jiyuan Wang, Miryung Kim
  Acceptance Rate: 24.5%
  
  The 29th ACM Joint European Software Engineering Conference
  and Symposium on the Foundations of Software Engineering, 13 pages, 2021
• Efficient Fuzz Testing for Apache Spark Using Framework Abstraction
  ICSE'21 Demonstration
  
  by Qian Zhang, Jiyuan Wang, Muhammad Ali Gulzar, Rohan Padhye, Miryung Kim
  Acceptance Rate: 37%
  
  The 43rd IEEE/ACM International Conference on Software Engineering,
  4 pages, Demonstrations, 2021
• BigFuzz: Efficient Fuzz Testing for Data Analytics using Framework Abstraction
  ASE'20
  
  by Qian Zhang, Jiyuan Wang, Muhammad Ali Gulzar, Rohan Padhye, Miryung Kim
  Acceptance Rate: 22.5%
  
  The 35th IEEE/ACM International Conference on Automated
  Software Engineering, 13 pages, 2021 [slides][video][tool]
• HeteroRefactor: Refactoring for Heterogeneous Computing with FPGA
  ICSE'20
  
  by Jason Lau*, Aishwarya Sivaraman*, Qian Zhang*, Muhammad Ali Gulzar,
  Acceptance Rate: 20.9%
  
  Jason Cong, Miryung Kim
  [* are equal co-first authors, ordered alphabetically by their last names.]
  The 42nd IEEE/ACM International Conference on Software Engineering,
  13 pages, 2020 [slides][video][tool]
• ApproxIt: A Quality Management Framework of Approximate Computing for Iterative Methods
  TCAD Journal'20
  
  by Qian Zhang, Qiang Xu
  The IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2020
• ARSketch: Sketch-Based User Interface for Augmented Reality Glasses
  ACM MM'20
  
  by Zhaohui Zhang*, Haichao Zhu*, Qian Zhang
  Acceptance Rate: 27%
  
  [* are equal co-first authors, ordered alphabetically by their last names.]
  The 28th ACM International Conference on Multimedia, 9 pages, 2020
• Lookup Table Allocation for Approximate Computing with Memory Under Quality Constraints
  DATE'18
  
  by Ye Tian, Qian Zhang, Ting Wang, Qiang Xu
  Acceptance Rate: 24%
  
  The Design, Automation and Test in Europe Conference and Exhibition, 2018
• ApproxLUT: A Novel Approximate Lookup Table-Based Accelerator
  ICCAD'17
  
  by Ye Tian, Ting Wang, Qian Zhang, Qiang Xu
  Acceptance Rate: 26%
  
  The IEEE/ACM International Conference on Computer-Aided Design, 2017
• ApproxQA: A Unified Quality Assurance Framework for Approximate Computing
  DATE'17
  
  by Ting Wang, Qian Zhang, Qiang Xu
  Acceptance Rate: 24%
  
  The Design, Automation and Test in Europe Conference and Exhibition, 2017
• ApproxEigen: An Approximate ComputingTechnique for Large-Scale Eigen-Decomposition
  ICCAD'15
  
  by Qian Zhang, Ye Tian, Ting Wang, Feng Yuan, Qiang Xu
  Acceptance Rate: 22.6%
  
  The IEEE/ACM International Conferenceon Computer-Aided Design, 2015
• ApproxANN: An Approximate ComputingFramework for Artificial Neural Network
  DATE'15
  
  by Qian Zhang, Ting Wang, Ye Tian, Feng Yuan, Qiang Xu
  Acceptance Rate: 22.4%
  
  The Design, Automation and Test in Europe Conference and Exhibition, 2015
• ApproxIt: An Approximate Computing Framework for Iterative Methods
  DAC'14
  
  by Qian Zhang, Feng Yuan, Rong Ye, Qiang Xu
  Acceptance Rate: 22.1%
  
  The IEEE/ACM Design Automation Conference, 2014
• ApproxMA: Approximate Memory Accessfor Dynamic Precision Scaling
  GVLSI'15
  
  by Ye Tian, Qian Zhang, Ting Wang, Feng Yuan, Qiang Xu
  invited
  
  The Great Lakes Symposium on VLSI, 2015
• On Effective and Efficient Quality Management for Approximate Computing
  ISLPED'16
  
  by Ting Wang, Qian Zhang, Nam Sung Kim, Qiang Xu
  Acceptance Rate: 32%
  
  The IEEE/ACM International Symposium on Low Power Electronicsand Design, 2016
• On Resilient Task Allocation and Scheduling with Uncertain Quality Checkers
  ASPDAC'17
  
  by Qian Zhang, Ting Wang, Qiang Xu
  Acceptance Rate: 30%
  
  The IEEE/ACM Asia and South Pacific Design Automation Conference, 2017
• ApproxMap: On Task Allocationand Scheduling for Resilient Applications
  ASPDAC'16
  
  by Yi Juan, Qian Zhang, Ye Tian, Ting Wang, Weichen Liu, Edwin H.-M. Sha, Qiang Xu
  Acceptance Rate: 31%
  
  The IEEE/ACM Asia and South Pacific DesignAutomation Conference, 2016
• On hybrid memory allocation for FPGA behavioral synthesis
  FPGA'14
  
  by Qian Zhang, Chenfei Ma, Qiang Xu
  poster track
  
  The ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2014