I’m a PhD researcher in the Programming Languages & Systems group at the University of Kent, supervised by Dr Stefan Marr.
My research focuses on a long-standing challenge: why Java profilers are so inaccurate, and why they disagree on what’s “hot.”
Sampling profilers often mislead developers, while traditional instrumentation can distort performance by orders of magnitude.

I’m developing a instrumentation for the Graal compiler that:

• 🧩 Inserts lightweight probes after all optimisation phases — leaving the compiler’s behaviour unchanged.

• ⚙️ Combines sampling to locate hot code with instrumentation to zoom in precisely.

Beyond building better profilers, I’m also designing techniques to measure profiler accuracy itself, introducing controlled slowdowns that reveal whether profilers can detect the true performance behavior.

🎯 Goal: Produce accurate profiles with minimal overhead — and a reliable way to prove it's accuracy.

• Burchell, H., & Marr, S. (2025).
  Divining Profiler Accuracy: An Approach to Approximate Profiler Accuracy Through Machine Code-Level Slowdown.
  Proceedings of the ACM on Programming Languages (OOPSLA ’25).

• Burchell, H., & Marr, S. (2025).
  Evaluating Candidate Instructions for Reliable Program Slowdown at the Compiler Level: Towards Supporting Fine-Grained Slowdown for Advanced Developer Tooling.
  17th ACM SIGPLAN International Workshop on Virtual Machines and Intermediate Languages (VMIL ’25), Singapore.

• Burchell, H., Larose, O., & Marr, S. (2024).
  Towards Realistic Results for Instrumentation-Based Profilers for JIT-Compiled Systems.
  21st ACM SIGPLAN International Conference on Managed Programming Languages and Runtimes (MPLR ’24), Vienna.

➡️ View all publications in KAR

If you’re interested in:

• Profilers and instrumentation
• CPU sampling and performance analysis
• Compiler-level slowdown

Feel free to get in touch!

📫 Email: h.burchell@kent.ac.uk

_{© 2025 Humphrey Burchell}