At Uber, speed and responsiveness of our mobile apps is of critical importance. At the same time, measuring and tuning mobile app performance brings many unique challenges, due to a huge variety of device capabilities and network conditions, differences in compilers and runtimes, and a large number of mutually-interacting external libraries and frameworks. In this talk, I will discuss some of these challenges, and present how our group is using static and dynamic analysis and custom optimizations to address them.
Manu Sridharan is a senior software engineer at Uber, leading a team focused on static analysis, software quality, and code optimization. He received his PhD from the University of California, Berkeley in 2007. He worked as a research staff member at IBM Research from 2008-2013 and as a senior researcher at Samsung Research America from 2013-2016. His research has drawn on, and contributed to, techniques in static analysis, dynamic analysis, and program synthesis, with applications to security, software quality, code refactoring, and software performance. His work has been incorporated into multiple commercial and open-source products, including IBM’s commercial security analysis tool, Samsung’s developer toolkit for Tizen, and Uber’s NullAway tool.