Qirun Zhang
Georgia Institute of Technology, GA·Computer Science·Early-career
Software we depend on every day can hide bugs. These are hard to find, and the tools developers use can be wrong themselves.
- Fields
Computer Science
- Topics
program analysis
static analysis
software reliability
- Grants
- 2 known grants, through Jun 2028
What they work on
- Characterize what the InterDyck graph abstraction can and cannot express. This is a graph model of programs with matched-edge patterns that represents program meaning for analysis.
- Develop efficient demand-driven and exhaustive algorithms for InterDyck-reachability. They answer whether one program point can reach another, to enable precise and scalable program analysis.
- Generate test programs that reveal incorrect debug information produced by optimizing compilers, the tools that translate and speed up source code.
- Produce comprehensive sequences of debugger actions to check compiler debug information on these test programs. Extend the validation techniques to multiple programming languages.
More about the research
Program analysis is the field of automatically reasoning about what a program will do. Analysis tools are used for testing, bug finding and quality assurance. Exact analysis is mathematically impossible in general, however, so practical tools approximate and can be imprecise. The research covers two related problems. The first is building more precise theoretical foundations for program analysis. The second is checking that compilers, the programs that translate source code into machine code, give debuggers correct information.
Why it matters
Reliable software underpins nearly everything society relies on. More precise and scalable program analysis could help developers find bugs before software is released. Validating compiler debug information could let developers trust their debuggers when fixing optimized code that is already in use. This could indirectly improve the quality of the software everyone relies on.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Shiyi Wei
University of Texas at Dallas, TX·Computer Science·Early-career
Identify hidden relationships among the configuration options of Android taint analysis tools, and present them in a unified, configuration-aware interface that makes tuning easier.
Xiaokang Qiu
Purdue University, IN·Computer Science·Early-career
Develop program synthesis algorithms that infer objective functions, library models and task decomposition themselves, so programmers need not hand-craft them, enabling scalable library-based synthesis.
Zachary Tatlock
University of Washington, WA·Computer Science
Speed up and extend the egg equality saturation library with relational e-matching (faster searches for places to apply rules), sketch-based extraction for choosing the best program, and destructive rewriting to control e-graph blow-up.
The school
Georgia Institute of Technology: 50 labs on PI Pages, $1.5B a year on research, 572 research doctorates a year.
Reach out
A start for your email. Fill in the brackets.