An efficient hybrid algorithm for incremental data flow analysis

Our exhaustive and incremental hybrid data flow analysis algorithms, based on iteration and elimination techniques, are designed for incremental update of a wide variety of monotone data flow problems in response to source program changes. Unlike previous incremental iterative methods, this incremental algorithm efficiently computes precise and correct solutions. We give theoretical results on the imprecision of restarting iteration for incremental update by fixed point iteration which provided motivation for our algorithm design. Described intuitively, the main algorithm idea is to factor the data flow solution on strong connected components of the flow graph into local and external parts, solving for the local parts by iteration and propagating these effects on the condensation of the flow graph to obtain the entire data flow solution. The incremental hybrid algorithm re-performs those algorithm steps affected by the program changes.