Research
My research lies at the intersection of software engineering, programming systems, and AI. My current interests include LLM serving systems and compilers, agentic software engineering, and testing and evaluation of AI systems. My research is funded by NSF, Cisco, UCR Senate, and SoCal OASIS.
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Testing and evaluation of AI systems
We develop testing and evaluation methods for real-world AI systems, including coding agents and physical AI systems in realistic deployment conditions.
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Agentic software engineering
We study how AI agents can support real software engineering workflows, including code generation, repair, testing, and long-horizon maintenance, with an emphasis on feedback and developer trust.
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LLM serving systems and compilers
We study compilation, optimization, testing, and debugging techniques for LLM serving stacks, spanning model transformations, runtime systems, and heterogeneous accelerator backends.
In prior work we also delivered novel testing and debugging tools for large-scale data analytics and heterogeneous computing.
Other Publications
EvoClaw: Evaluating AI Agents on Continuous Software Evolution, Gangda Deng*, Zhaoling Chen*, Zhongming Yu, Haoyang Fan, Yuhong Liu, Yuxin Yang, Dhruv Parikh, Rajgopal Kannan, Le Cong, Mengdi Wang, Qian Zhang, Viktor Prasanna, Xiangru Tang, Xingyao Wang.
[* are equal co-first authors, ordered alphabetically by their first names.]
2026 [leaderboard][data][code]Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement, Zhaorui Yang, Yuxin Qiu, Haichao Zhu, Qian Zhang, International Conference on Software Maintenance and Evolution (ICSME), 2025
Efficient Test Generation for Dynamic Behaviors Leveraging Token-Level Input Commonalities, Yuxin Qiu and Qian Zhang, The 33rd ACM International Conference on the Foundations of Software Engineering
5 pages, 2025
DuoReduce: Bug Isolation for Multi-Layer Extensible Compilation, Jiyuan Wang, Yuxin Qiu, Ben Limpanukorn, Hong Jin Kang, Qian Zhang, Miryung Kim, The 33rd ACM International Conference on the Foundations of Software Engineering
21 pages, 2025
Calico: Automated Knowledge Calibration and Diagnosis for Elevating AI Mastery in Code Tasks, Yuxin Qiu, Jie Hu, Qian Zhang, Heng Yin, The ACM SIGSOFT International Symposium on Software Testing and Analysis,
MetaSim: A search engine for finding Similar GitHub Repositories, Md Rayhanul Masud, Md Omar Faruk Rokon, Qian Zhang, Michalis Faloutsos, The 40th IEEE International Conference on Software Maintenance and Evolution,
5 pages, Demonstrations, 2024
Testing AI Systems Leveraging Graph Perturbation, Zhaorui Yang, Haichao Zhu, Qian Zhang, The ACM International Conference on the Foundations of Software Engineering, Poster, 2024
Who is Creating Malware Repositories on GitHub and Why?, Nishat Ara Tania, Md Rayhanul Masud, Md Omar Faruk Rokon, Qian Zhang, Michalis Faloutsos, The Companion Proceedings of the ACM Web Conference 2024, 4 pages, 2024
Augmenting Greybox Fuzzing with Generative AI, Jie Hu, Qian Zhang, and Heng Yin
Leveraging Hardware Probes and Optimizations for Accelerating Fuzz Testing of Heterogeneous Applications, Jiyuan Wang, Qian Zhang, Hongbo Rong, Harry Xu, and Miryung Kim, 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 Test Generation and Program Repair, 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, Jiyuan Wang, Qian Zhang, Harry Xu, Miryung Kim, The 36th IEEE/ACM International Conference on Automated
Software Engineering, 13 pages, 2021
HeteroFuzz: Fuzz Testing to Detect Platform Dependent Divergence, Qian Zhang, Jiyuan Wang, Miryung Kim, 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, Qian Zhang, Jiyuan Wang, Muhammad Ali Gulzar, Rohan Padhye, Miryung Kim, The 43rd IEEE/ACM International Conference on Software Engineering,
4 pages, Demonstrations, 2021
BigFuzz: Efficient Fuzz Testing for Data Analytics using Framework Abstraction, Qian Zhang, Jiyuan Wang, Muhammad Ali Gulzar, Rohan Padhye, Miryung Kim, The 35th IEEE/ACM International Conference on Automated
HeteroRefactor: Refactoring for Heterogeneous Computing with FPGA, Jason Lau*, Aishwarya Sivaraman*, Qian Zhang*, Muhammad Ali Gulzar, Jason Cong, Miryung Kim, The 42nd IEEE/ACM International Conference on Software Engineering
[* are equal co-first authors, ordered alphabetically by their last names.]
ApproxIt: A Quality Management Framework of Approximate Computing for Iterative Methods, 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, Zhaohui Zhang*, Haichao Zhu*, Qian Zhang, The 28th ACM International Conference on Multimedia
[* are equal co-first authors, ordered alphabetically by their last names.]
9 pages, 2020
Lookup Table Allocation for Approximate Computing with Memory Under Quality Constraints, Ye Tian, Qian Zhang, Ting Wang, Qiang Xu, The Design, Automation and Test in Europe Conference and Exhibition, 2018
ApproxLUT: A Novel Approximate Lookup Table-Based Accelerator, Ye Tian, Ting Wang, Qian Zhang, Qiang Xu, The IEEE/ACM International Conference on Computer-Aided Design, 2017
ApproxQA: A Unified Quality Assurance Framework for Approximate Computing, Ting Wang, Qian Zhang, Qiang Xu, The Design, Automation and Test in Europe Conference and Exhibition, 2017
ApproxEigen: An Approximate ComputingTechnique for Large-Scale Eigen-Decomposition, Qian Zhang, Ye Tian, Ting Wang, Feng Yuan, Qiang Xu, The IEEE/ACM International Conferenceon Computer-Aided Design, 2015
ApproxANN: An Approximate ComputingFramework for Artificial Neural Network, Qian Zhang, Ting Wang, Ye Tian, Feng Yuan, Qiang Xu, The Design, Automation and Test in Europe Conference and Exhibition, 2015
ApproxIt: An Approximate Computing Framework for Iterative Methods, Qian Zhang, Feng Yuan, Rong Ye, Qiang Xu, The IEEE/ACM Design Automation Conference, 2014
ApproxMA: Approximate Memory Accessfor Dynamic Precision Scaling, Ye Tian, Qian Zhang, Ting Wang, Feng Yuan, Qiang Xu, The Great Lakes Symposium on VLSI, 2015
Invited track
On Effective and Efficient Quality Management for Approximate Computing, Ting Wang, Qian Zhang, Nam Sung Kim, Qiang Xu, The IEEE/ACM International Symposium on Low Power Electronicsand Design, 2016
On Resilient Task Allocation and Scheduling with Uncertain Quality Checkers, Qian Zhang, Ting Wang, Qiang Xu, The IEEE/ACM Asia and South Pacific Design Automation Conference, 2017
ApproxMap: On Task Allocationand Scheduling for Resilient Applications, Yi Juan, Qian Zhang, Ye Tian, Ting Wang, Weichen Liu, Edwin H.-M. Sha, Qiang Xu, The IEEE/ACM Asia and South Pacific DesignAutomation Conference, 2016
On hybrid memory allocation for FPGA behavioral synthesis, Qian Zhang, Chenfei Ma, Qiang Xu, The ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2014
Poster track