计算机软件新技术国家重点实验室   

摘 要：

     Points-to analysis addresses a fundamental problem in program analysis: determining statically which objects a variable or reference can point to. As a fundamental technique, many real-world  clients  such  as  bug  detection, security analysis, program understanding, compiler optimization and program verification,  depend on the results of points-to analysis. A long-standing problem in points-to analysis is the balance between precision and efficiency. In this talk, I will present our two work, Bean and Mahjong, which aim to improve both ends of the balance respectively. The two related papers have been published at SAS'16 and PLDI'17. We extensively evaluate Bean and Mahjong against the state-of-the-art points-to analysis for Java with large real-world Java applications and library.  The results demonstrate that both Bean and Mahjong have met their goals of design. Bean has succeeded in making points-to analysis more precise at only small increases in analysis cost. Mahjong enables points-to analysis to run significantly faster while achieving nearly the same precision for type-dependent clients.  We have released Bean and Mahjong as open-source tools.

报告人简介:

   ian Tan is a postdoc at Department of Computer Science, Aarhus University. He received his Ph.D. degree in Computer Science from University of New South Wales, Australia in 2017. He is particularly interested in developing program analysis techniques and tools for solving the problems in the fields of programming language and software engineering. Tian has published papers on top computer science venues such as PLDI, OOPSLA, TOSEM and ESEC/FSE. He recently serves as the committee member of PLDI'19 SRC, OOPSLA'19 AEC, and the reviewer for TOPLAS and ISSTA.

报告人：谭添Aarhus University

时间：月5日  11:00-12:00