efficient online detection of dynamic control dependence
Capturing dynamic control dependence is critical for many dynamic program analysis such as dynamic slicing, dynamic information flow, and data lineage computation. Existing algorithms are mostly a simple runtime translation of the static definition, which fails to capture certain dynamic properties by its nature, leading to inefficiency. In this paper, we propose a novel online detection technique for dynamic control dependence. The technique is based upon a new definition, which is equivalent to the existing one in the intraprocedural case but it enables an efficient detection algorithm. The new algorithm naturally and efficiently handles interprocedural dynamic control dependence even in presence of irregular control flow. Our evaluation shows that the detection algorithm slows down program execution by a factor of 2.57, which is 2.54 times faster than the existing algorithm that was used in prior work.
dynamic control dependence dynamic information flow irregular control flow dynamic post-dominance dynamic program slicing