Data-Flow Analysis for Hot-Spot Program Optimization

A hot spot of a program is a program region, whose execution time crucially impacts the overall execution time of the program. A hot spot can often be optimized without fully analyzing the whole program. This is supported by approaches for demand-driven data-flow analysis. Particularly successful in practice turned out to be an approach based on reverse data-flow analysis. In this paper, we reconsider this approach. By recalling the Reverse Safety and Coincidence Theorem and the Link Theorem we highlight the duality of classical and reverse data-flow analysis and their relationship to each other. This addresses a common gap in previous presentations of this approach and sheds light on the formal foundation underlying the construction of correct and precise demand-driven data-flow analyses based on reverse data-flow analysis. We illustrate the usability of this approach for hot-spot program optimization. It is useful, however, for other applications, too, such as just-in-time compilation and debugging.