How is aliasing used in systems software?

We present a study of all sources of aliasing in over one million lines of C code, identifying in the process the common patterns of aliasing that arise in practice. We find that aliasing has a great deal of structure in real programs and that just nine programming idioms account for nearly all aliasing in our study. Our study requires an automatic alias analysis that both scales to large systems and has a low false positive rate. To this end, we also present a new context-, flow-, and partially path-sensitive alias analysis that, together with a new technique for object naming, achieves a false aliasing rate of 26.2%on our benchmarks.

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