WALA Tutorial at PLDI 2016 - overview
PLDI 2016 Tutorial
Cross-platform analysis of mobile apps using the WALA framework
There are multiple mobile platforms, such as iOS, Android, Tizen, Windows Phone and Firefox OS. And hybrid apps are supported on some platforms too. Each has app stores with numerous apps, written in different languages and for different architectures. Many concerns are shared across all apps: e.g. battery consumption (does the app drain the phone?), privacy (does it improperly share information), security (is the app malicious?), stability (does it handle exceptional inputs correctly?), etc.
Program analysis can address these concerns, but currently requires different analysis implementations for different platforms; this is time consuming and complicates cross-platform studies.
The Watson Libraries for Analysis (WALA) framework supports the languages, and semantic models, underlying all of the above the platforms, enabling one to write the analysis algorithm once and apply it to all these platforms.
In this tutorial, we walk the attendees through this process. We start with a technical overview of the WALA framework and its support for analysis of mobile code. Then, we briefly present the different platforms, including writing a common concrete app. Finally, we interactively create an analysis algorithm, using the foundations from the first part, and apply it to an app written in the second part across all platforms.
Julian Dolby is a Research Staff Member at the IBM Thomas J. Watson Research Center, where he works on program analysis for a range of programming languages. He is one of the original creators of WALA; his recent WALA work has focused on creating the WALA Mobile infrastructure. He has co-presented tutorials on WALA at several PLDI conferences, and co-organized the Workshop on WALA at PLDI 2015.
Sukyoung Ryu (류석영) is an associate professor at Korea Advanced Institute of Science and Technology (KAIST). Before joining KAIST, she was a Research Associate at Harvard and a Member of Technical Staff at Sun Microsystems Laboratories. She co-organized a Fortress tutorial at PLDI 2006, a 2014 Big Data Workshop in Hong Kong, and Workshop on WALA (WoW) 2015 at PLDI. Her recent research focuses on designing and developing the publicly-available Scalable Analysis Framework for ECMAScript (SAFE) to help end-users use web applications more securely.
Omer Tripp (עומר) is a research staff member and technical lead at the IBM TJ Watson Research Center, where he is currently leading a research project on mobile reputation analysis. More generally, Omer’s recent research is focused on program analysis and its applications in the mobile space, including in particular testing and verification of security and privacy properties in mobile environments. Omer has co-organized the Workshop on Programming Languages and Analysis for Securtiy (PLAS) in 2014, and is a co-organizer of the Workshop on Dynamic Analysis (WODA) in 2015.