paperJune 2026Unreviewed

MPC-Patch-Bench: Security-Aware LLM Code Patch for Multi-Party Computation

Yukuan Zhang, Mengxin Zheng, Qian Lou

Abstract

Repository-level benchmarks for evaluating Large Language Model (LLM) code repair on Secure Multi-Party Computation (MPC) software do not yet exist, and directly transplanting general-purpose benchmarks such as SWE-bench fails on three structural fronts: (i) MPC repositories are dominated by generic Python infrastructure rather than cryptographic logic; (ii) high-value MPC fixes lack the standardized tests rigid extraction pipelines require; and (iii) standard fail-to-pass evaluation is insuffic

Cite

@misc{zhang2026mpcpatchbench,
  title = {{MPC-Patch-Bench: Security-Aware LLM Code Patch for Multi-Party Computation}},
  author = {Yukuan Zhang and Mengxin Zheng and Qian Lou},
  year = {2026},
  month = jun,
  eprint = {2606.11416},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.11416}
}