Faster Variational Execution with Transparent Bytecode Transformation
Variational execution is a novel dynamic analysis technique for exploring highly configurable systems and accurately tracking information flow. It is able to efficiently analyze many configurations by aggressively sharing redundancies of program executions. The idea of variational execution has been demonstrated to be effective in exploring variations in the program, especially when the configuration space grows out of control. Existing implementations of variational execution often require heavy lifting of the runtime interpreter, which is painstaking and error-prone. Furthermore, the performance of this approach is suboptimal. For example, the state-of-the-art variational execution interpreter for Java, VarexJ, slows down executions by 100 to 800~times over a single execution for small to medium size Java programs. Instead of modifying existing JVMs, we propose to transform existing bytecode to make it variational, so it can be executed on an unmodified commodity JVM. Our evaluation shows a dramatic improvement on performance over the state-of-the-art, with a speedup of up to 46 times, and high efficiency in sharing computations.
Wed 7 NovDisplayed time zone: Guadalajara, Mexico City, Monterrey change
13:30 - 15:00 | |||
13:30 22mTalk | A Derivation Framework for Dependent Security Label Inference OOPSLA | ||
13:52 22mTalk | MadMax: Surviving Out-of-Gas Conditions in Ethereum Smart Contracts OOPSLA Neville Grech University of Athens, Michael Kong University of Sydney, Anton Jurisevic University of Sydney, Lexi Brent University of Sydney, Bernhard Scholz The University of Sydney, Yannis Smaragdakis University of Athens Link to publication Pre-print File Attached | ||
14:15 22mTalk | Faster Variational Execution with Transparent Bytecode Transformation OOPSLA Chu-Pan Wong Carnegie Mellon University, Jens Meinicke Magdeburg University, Lukas Lazarek , Christian Kästner Carnegie Mellon University | ||
14:37 22mTalk | Secure Serverless Computing Using Dynamic Information Flow Control OOPSLA Kalev Alpernas Tel Aviv University, Cormac Flanagan University of California, Santa Cruz, Sadjad Fouladi Stanford University, Leonid Ryzhyk VMware Research, Mooly Sagiv Tel Aviv University, Thomas Schmitz , Keith Winstein Stanford University |