Abstract
Reflection has always been an obstacle both for sound and for effective under-approximate pointer analysis for Java applications. In pointer analysis tools, reflection is either ignored or handled partially, resulting in missed, important behaviors. In this paper, we present our findings on reflection usage in Java benchmarks and applications. Guided by these findings, we introduce a static reflection analysis, called Elf, by exploiting a self-inferencing property inherent in many reflective calls. Given a reflective call, the basic idea behind Elf is to automatically infer its targets (methods or fields) based on the dynamic types of the arguments of its target calls and the downcasts (if any) on their returned values, if its targets cannot be already obtained from the Class, Method or Field objects on which the reflective call is made. We evaluate Elf against Doop’s state-of-the-art reflection analysis performed in the same context-sensitive Andersen’s pointer analysis using all 11 DaCapo benchmarks and two applications. Elf can make a disciplined tradeoff among soundness, precision and scalability while also discovering usually more reflective targets. Elf is useful for any pointer analysis, particularly under-approximate techniques deployed for such clients as bug detection, program understanding and speculative compiler optimization.
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Li, Y., Tan, T., Sui, Y., Xue, J. (2014). Self-inferencing Reflection Resolution for Java. In: Jones, R. (eds) ECOOP 2014 – Object-Oriented Programming. ECOOP 2014. Lecture Notes in Computer Science, vol 8586. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44202-9_2
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