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The Complexity of Andersen's Analysis in Practice
[chapter]

2009
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Lecture Notes in Computer Science
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While the tightest proven worst-case complexity for Andersen's points-to analysis is nearly cubic, the analysis seems to scale better on real-world codes. We examine algorithmic factors that help account for this gap. In particular, we show that a simple algorithm can compute Andersen's analysis in worst-case quadratic time as long as the input program is k-sparse, i.e., it has at most k statements dereferencing each variable and a sparse flow graph. We then argue that for stronglytyped

doi:10.1007/978-3-642-03237-0_15
fatcat:drvgvornknhlvabzp5eqldoenu