We propose a definition of parallel state, derive a phase space from this state, and calculate the entropy of states and full executions using combinatorial analysis. A main contribution of this work is the introduction of an experimentally measurable phase space, which we then use to analyze execution states, ensembles of states, and ensembles of complete executions. We show that the entropy analysis reveals both expected and unexpected features of execution, and application of principal component analysis shows capability to extract execution details at the level of individual process states, as well as reveal hardware properties such as network or memory communications.