Pervasive use of pointers in large-scale real-world applications continues to make points-to analysis an important optimization-enabler. Rapid growth of software systems demands a scalable pointer analysis algorithm. A typical inclusion-based points-to analysis iteratively evaluates constraints and computes a points-to solution until a fix-point. In each iteration, points-to information is propagated across directed edges in a constraint graph G and more edges are added by processing the points-to constraints. The authors observe that prioritizing the order in which the information is processed within each of the above two steps can lead to efficient execution of the points-to analysis.