Towards Comparing and Combining Points-to Analyses

Points-to information is the basis for many analyses and transformations, e.g., for program understanding and optimization. To justify new analysis techniques, they need to be compared to the state of the art regarding their accuracy and efficiency. Usually, benchmark suites are used to experimentally compare the different techniques. In this paper, we show that the accuracy of two analyses can only be compared in restricted cases, as there is no benchmark suite with exact points-to information, no gold standard, and it is hard to construct one for realistic programs. We discuss the challenges and possible traps that may arise when comparing different points-to analyses directly with each other, and with over- and under-approximations of a gold standard. Moreover, we discuss how different points-to analyses can be combined to a more precise one. We complement the paper with experiments comparing and combining different static and dynamic points-to analyses.