Static and Dynamic Program Analysis: Synergies and Applications
- Mayur Naik | Stanford University
Modern computing platforms pose unprecedented challenges to productively building reliable, scalable, and energy-efficient software. I will show how static and dynamic program analysis can be combined in novel ways to effectively address these challenges. My talk will focus on three challenges: seamlessly partitioning programs for rich mobile computing, automatically estimating program performance for predictable cloud computing, and scalably verifying programs for reliable parallel computing. I will demonstrate how we can significantly reduce energy consumption on mobile devices by offloading compute-intensive parts of rich apps to the cloud, how we can automatically predict the running time of general-purpose programs accurately and efficiently, and how we can scalably prove vast parts of real-world concurrent programs thread-safe while exposing harmful concurrency bugs in the remaining parts.
Speaker Details
Mayur Naik is a researcher at Intel Labs, Berkeley. His research interests lie in the areas of programming languages and software engineering, with a current focus on its applications to problems in cloud, mobile, and parallel computing. He obtained his PhD in Computer Science from Stanford University in 2007.
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Jeff Running
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