We propose a general framework to build certified proofs of distributed self-stabilizing algorithms with the proof assistant Coq. We first define in Coq the locally shared memory model with composite atomicity, the most commonly used model in the self-stabilizing area. We then validate our framework by certifying a non trivial part of an existing silent self-stabilizing algorithm which builds a $k$-clustering of the network. We also certify a quantitative property related to the output of this algorithm. Precisely, we show that the computed $k$-clustering contains at most $\lfloor \frac{n-1}{k+1} \rfloor + 1$ clusterheads, where $n$ is the number of nodes in the network. To obtain these results, we also developed a library which contains general tools related to potential functions and cardinality of sets.

@article{AltisenCD17,
  title = {A Framework for Certified Self-Stabilization},
  author = {Karine Altisen and Pierre Corbineau and Stephane Devismes},
  journal = {Logical Methods in Computer Science},
  volume = {Volume 13, Issue 4},
  year = {2017},
  doi = {10.23638/lmcs-13(4:14)2017}
}