计算机软件新技术国家重点实验室

摘 要：

Traditional context-sensitive pointer analysis is hard to scale for large and complex Java programs. To address this issue, a series of selective context-sensitivity approaches have been proposed and exhibit promising results. In this work, we move one step further towards producing highly-precise pointer analyses for hard-to-analyze Java programs by presenting the Unity-Relay framework, which takes selective context sensitivity to the next level. Briefly, Unity-Relay is a one-two punch: given a set of different selective context-sensitivity approaches, say S = S1, …, Sn, Unity-Relay first provides a mechanism (called Unity) to combine and maximize the precision of all components of S. When Unity fails to scale, Unity-Relay offers a scheme (called Relay) to pass and accumulate the precision from one approach Si in S to the next, Si+1, leading to an analysis that is more precise than all approaches in S. As a proof-of-concept, we instantiate Unity-Relay into a tool called Baton and extensively evaluate it on a set of hard-to-analyze Java programs, using general precision metrics and popular clients. Compared with the state of the art, Baton achieves the best precision for all metrics and clients for all evaluated programs. The difference in precision is often dramatic—up to 71% of alias pairs reported by previously-best algorithms are found to be spurious and eliminated.

报告人简介：

谭添，南京大学计算机科学与技术系助理研究员。2017年于新南威尔士大学获博士学位，2013年于西北工业大学获学士学位，2017至2019年于奥胡斯大学从事博士后研究工作。研究方向为程序分析与程序设计语言。研究成果发表在TOPLAS、PLDI、OOPSLA、ECOOP、TOSEM、FSE等相关领域的高水平期刊与会议。

时间：12月14日(星期二) 12:30

地点：计算机科学技术楼111室

腾讯会议ID：431 436 824