For concurrent and parallel languages, may-happen-in-parallel (MHP) analysis is useful as a basis for tools such as data race detectors. While many approximate static MHP analyses exist, researchers have published only a few papers on decidability results for MHP analysis. We study MHP analysis for a model of X10, a parallel language with async-finish parallelism. For programs with procedures, we show that the MHP decision problem is decidable in linear time, and hence the set of pairs of actions that may happen in parallel can be computed in cubic time. For programs without procedures, we present a practical recur-sive decision procedure that does multiple-query MHP analysis in cubic time. Our results indicate that MHP analysis is tractable for a standard storeless abstraction of X10 programs.