Existing deep neural network (DNN) frameworks optimize the computation graph of a DNN
by applying graph transformations manually designed by human experts. This approach …

We designed, implemented, and deployed Alive2: a bounded translation validation tool for
the LLVM compiler's intermediate representation (IR). It limits resource consumption by, for …

We address the problem of code search in executables. Given a function in binary form and
a large code base, our goal is to statically find similar functions in the code base. Towards …

The aggressive optimization of floating-point computations is an important problem in high-
performance computing. Unfortunately, floating-point instruction sets have complicated …

We introduce a robust semantics-driven technique for program equivalence checking. Given
two functions we find a trace alignment over a set of concrete executions of both programs …

We present a scalable approach for establishing similarity between stripped binaries (with
no debug information). The main challenge in binary similarity, is to establish similarity even …

Hunting binary code difference without source code (ie, binary diffing) has compelling
applications in software security. Due to the high variability of binary code, existing solutions …

If we can automatically derive compiler optimizations, we might be able to sidestep some of
the substantial engineering challenges involved in creating and maintaining a high-quality …

We address the problem of verifying k-safety properties: properties that refer to k interacting
executions of a program. A prominent way to verify k-safety properties is by self composition …

Abstract Partially-Observable Markov Decision Processes (POMDPs) are a well-known
stochastic model for sequential decision making under limited information. We consider the …