Everyone uses math libraries. Surprisingly, mainstream math libraries do not produce correct results for several thousands of inputs. Developers are seldom aware of them, which affects reproducibility and portability. We describe our new method for synthesizing elementary functions that produces correct results for all inputs but is also significantly faster than the state of the art libraries, which have been optimized for decades.
Sensitivity properties study how the output of a program changes when we make small changes to its input. How can we reason about sensitivity of programs that have probabilistic behavior?
Defending cryptographic code from Spectre attacks is difficult. Blade is a fully automatic approach to eliminate speculative leaks provably and efficiently.
The cost of inference is the primary barrier for wider application of probabilistic programming languages. How can we scale inference to truly huge programs?
SIGPLAN organizes conferences, funds travel for students, and gives awards in the area of programming languages.