Data mining based decomposition for assume-guarantee reasoning

Automated compositional reasoning using assume-guarantee rules plays a key role in large system verification. A vexing problem is to discover fine decomposition of system contributing to appropriate assumptions. We present an automatic decomposition approach in compositional reasoning verification. The method is based on data mining algorithms. An association rule algorithm is harnessed to discover the hidden rules among system variables. A hypergraph partitioning algorithm is proposed to incorporate these rules as weight constraints for system variable clustering. The experiments demonstrate that our strategy leads to order-of-magnitude speedup over previous.