Changkun Guan Changkun Guan

Changkun Guan

Ph.D. student in Operations Research at Georgia Tech's H. Milton Stewart School of Industrial and Systems Engineering (ISyE).

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Optimal Covering Arrays & Combinatorial Testing

Covering arrays are a core tool in combinatorial interaction testing: compact test suites that guarantee coverage of all parameter-value interactions up to a given strength. This project studied how to optimize covering arrays with binary parameters under constraints.

Key contributions:

  • Worked on proofs about the structure of optimal covering arrays under constraints
  • Implemented integer programming models in Gurobi and algorithms in Python
  • Proposed the project and received funding from Bucknell’s Program for Undergraduate Research

Principal Investigator: Dr. Thiago Serra

The project culminated in Optimal Combinatorial Testing with Constraints: The Balancing Act (2026, with Thiago Serra, Hunter Gehman, Sumit Dhar, Mikey Ferguson, John Hooker, and Marcel Schoppers), which contrasts unconstrained and constrained pairwise-coverage testing and proposes the first exact integer-programming algorithm alongside a fast, often-optimal heuristic.