Accelerating Dynamic Software Analyses
Dynamic software analyses are powerful mechanisms for finding software errors. Unfortunately, their high performance overheads stymie their adoption. This talk discusses techniques for accelerating such tools in an effort to make them available to beta testers and end users.
One method of reducing these slowdowns, “on-demand analysis,” uses simple hardware features to inform an analysis tool that an interesting event has occurred. By disabling the tool during uninteresting periods, it is possible to significantly reduce that tool’s overall slowdown.
Another method is to sample the analyses, meaning individual users test a small portions of a program each execution. While, individually, they may miss errors, a large population will see many errors in aggregate. These users can report the potential software errors to developers, while collectively observing more program state space than any individual tester would ever see.
Speaker Details
Joseph Greathouse is a PhD candidate in the Department of Electrical Engineering and Computer Science at the University of Michigan. His research focuses on architectural mechanisms that yield better, more correct, software and hardware. He received a BS in Computer Engineering from the University of Illinois at Urbana-Champaign.
- Series:
- Microsoft Research Talks
- Date:
- Speakers:
- Joseph Greathouse
- Affiliation:
- University of Michigan
-
-
Jeff Running
-
-
Series: Microsoft Research Talks
-
Decoding the Human Brain – A Neurosurgeon’s Experience
Speakers:- Pascal Zinn,
- Ivan Tashev
-
-
-
-
Galea: The Bridge Between Mixed Reality and Neurotechnology
Speakers:- Eva Esteban,
- Conor Russomanno
-
Current and Future Application of BCIs
Speakers:- Christoph Guger
-
Challenges in Evolving a Successful Database Product (SQL Server) to a Cloud Service (SQL Azure)
Speakers:- Hanuma Kodavalla,
- Phil Bernstein
-
Improving text prediction accuracy using neurophysiology
Speakers:- Sophia Mehdizadeh
-
-
DIABLo: a Deep Individual-Agnostic Binaural Localizer
Speakers:- Shoken Kaneko
-
-
Recent Efforts Towards Efficient And Scalable Neural Waveform Coding
Speakers:- Kai Zhen
-
-
Audio-based Toxic Language Detection
Speakers:- Midia Yousefi
-
-
From SqueezeNet to SqueezeBERT: Developing Efficient Deep Neural Networks
Speakers:- Sujeeth Bharadwaj
-
Hope Speech and Help Speech: Surfacing Positivity Amidst Hate
Speakers:- Monojit Choudhury
-
-
-
-
-
'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project
Speakers:- Peter Clark
-
Checkpointing the Un-checkpointable: the Split-Process Approach for MPI and Formal Verification
Speakers:- Gene Cooperman
-
Learning Structured Models for Safe Robot Control
Speakers:- Ashish Kapoor
-