Fighting Software Inefficiency Through Automated Bug Detection
Developers frequently use inefficient code sequences that could be fixed by simple patches. These inefficient code sequences can cause significant performance degradation and resource waste, referred to as performance bugs. Meager increases in single threaded performance in the multi-core era and increasing emphasis on energy efficiency call for more effort in tackling performance bugs. This talk will present an overview of our group’s work in understanding, detecting, and fixing performance bugs. I will explain how we refine our bug-detector designs through a series of projects, and eventually detect and fix hundreds of performance bugs in the latest versions of widely used open-source applications.
Shan Lu is an Associate Professor in the Department of Computer Science at the University of Chicago.
She received her Ph.D. at University of Illinois, Urbana-Champaign, in 2008. She was the Clare Boothe Luce Assistant Professor of Computer Sciences at University of Wisconsin, Madison, from 2009 to 2014. Her research focuses on software reliability, particularly detecting, diagnosing, and fixing concurrency bugs and performance bugs in large software systems.
Shan has won Alfred P. Sloan Research Fellow in 2014, Distinguished Alumni Educator Award from Department of Computer Science at University of Illinois in 2013, and NSF Career Award in 2010.
Her co-authored papers won two ACM-SIGSOFT Distinguished Paper Awards at ICSE 2015 and FSE 2014, one Best Paper Award at USENIX FAST in 2013, an ACM-SIGPLAN Research Highlight Award in 2011, and an IEEE Micro Top Picks in 2006.
Shan serves as the Vice Chair of ACM-SIGOPS in 2015–2018, and the Information Director of ACM-SIGOPS in 2013–2015. She also served as the technical program co-chair for USENIX Annual Technical Conference in 2015.
Tue 14 JunDisplayed time zone: Tijuana, Baja California change
10:30 - 12:00
Technical TalksPLMW@PLDI at Grand Ballroom Santa Ynez
|Fighting Software Inefficiency Through Automated Bug Detection|
Shan Lu University of ChicagoMedia Attached
|The Truth, the Whole Truth, and Nothing but the Truth: A Pragmatic Guide to Assessing Empirical Evaluations|
Steve Blackburn Australian National UniversityMedia Attached
|Approximate Computing: it's better than good, it's good enough!|
Michael Carbin MITMedia Attached