Making k-Object-Sensitive Pointer Analysis More Precise with Still k-Limiting Making k-Object-Sensitive Pointer Analysis More Precise with Still k-Limiting
Bean is an open-source tool introduced in our paper titled "Making k-Object-Sensitive Pointer Analysis More Precise with Still k-Limiting", SAS'2016. Bean is able to improve the precision of k-object-sensitive pointer analysis by avoiding the redundant context elements automatically. This approach can also be easily applied to other context-sensitive analyses such as k-CFA and type-sensitive analysis.
We implement Bean as a standalone tool in Java. To demonstrate the usefulness of Bean on improving the precision of pointer analysis, we have integrated Bean with Doop, a state-of-the-art context-sensitive pointer analysis framework for Java. Bean was developed by Tian Tan and Yue Li.
The tar.gz file includes the source code, executable program and a tutorial of Bean.