JavaScript Pointer Analysis with Adaptive Heap Abstraction
Wenyuan Xu, Anders Møller
摘要
The conventional approach to represent objects in static program analysis is to use allocation-site abstraction. This design choice may lead to redundant computations when many abstract objects are similar. Existing mechanisms that aim to merge such objects are not effective for JavaScript. We propose a novel adaptive heap abstraction technique that during analysis discovers and merges similar abstract objects, thereby reducing the analysis complexity while preserving most of the precision.
The technique has been implemented in a state-of-the-art program analyzer for JavaScript. On a collection of 96 challenging programs, it yields a 2X speedup on average (up to 17X) with a negligible loss of precision. The experimental results also show the effects of various analysis configurations.
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