Making it practical and effective: Fast and precise May-Happen-in-Parallel analysis

May-Happen-in-Parallel (MHP) analysis is a very important and fundamental mechanism to facilitate concurrent program analysis. But the limitation of its efficiency keep it away from being practical and effective in analyzing large scale real world concurrent programs. We proposed a novel MHP algorithm by performing a reachability analysis on a so-called parallel reachability graph of a program. The MHP algorithm mainly comprises two phases: pre-computation of initial MHP information and top-down propagation of this information along the parallel reachability graph. Our algorithm is fast as it has a low complexity O(|N|+|E|), in which N is the number of nodes in the parallel reachability graph and E is the number of edges in this graph. Our preliminary experiment on 13 concurrent programs indicates that our approach is extremely faster than two state-of-art approaches, respectively achieving a relative geometry average speed up of 395.53× and 136.37×, while yielding the same precision with these two approaches.