Swift is an open-source programming language and Apple's recommended choice for app development. Given the global widespread use of Apple devices, the ability to analyze Swift programs has significant impact on millions of users. Although static analysis frameworks exist for various computing platforms, there is a lack of comparable tools for Swift. While LLVM and Clang support some analyses for Swift, they are either primarily dynamic analyses or not suitable for deeper analyses of Swift programs such as taint tracking. Moreover, other existing tools for Swift only help enforce code styles and best practices.
In this paper, we present SWAN, an open-source framework that allows robust program analyses of Swift programs using IBM's T.J. Watson Libraries for Analysis (WALA). To provide a wide range of analyses for Swift, SWAN leverages the well-established libraries in WALA. SWAN is publicly available at https://github.com/themaplelab/swan. We have also made a screencast available at https://youtu.be/AZwfhOGqwFs.
Fri 13 Nov Times are displayed in time zone: (UTC) Coordinated Universal Time change
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ARDiff: Scaling Program Equivalence Checking via Iterative Abstraction and Refinement of Common Code
Sahar BadihiUniversity of British Columbia, Canada, Faridah AkinotchoUniversity of British Columbia, Canada, Yi LiNanyang Technological University, Singapore, Julia RubinUniversity of British Columbia, CanadaDOI Pre-print
|01:03 - 01:04|
Vaibhav SharmaUniversity of Minnesota, USA, Soha HusseinUniversity of Minnesota, USA / Ain Shams University, Egypt, Michael WhalenUniversity of Minnesota, USA, Stephen McCamantUniversity of Minnesota, USA, Willem VisserStellenbosch University, South AfricaDOI
|01:05 - 01:06|
Wen Li, Haipeng CaiWashington State University, USA, Yulei SuiUniversity of Technology Sydney, David ManzPacific Northwest National Laboratory, USADOI
|01:07 - 01:08|
Daniil TiganovUniversity of Alberta, Canada, Jeff ChoUniversity of Alberta, Karim AliUniversity of Alberta, Julian DolbyIBM Research, USADOI
|01:09 - 01:10|
Yizhuo ZhaiUniversity of California at Riverside, USA, Yu HaoUniversity of California at Riverside, USA, Hang ZhangUniversity of California at Riverside, USA, Daimeng WangUniversity of California at Riverside, USA, Chengyu SongUniversity of California at Riverside, USA, Zhiyun QianUniversity of California at Riverside, USA, Mohsen LesaniUniversity of California at Riverside, USA, Srikanth V. KrishnamurthyUniversity of California at Riverside, USA, Paul YuU.S. Army Research Laboratory, USADOI
|01:11 - 01:30|