A crucial performance bottleneck in most interprocedural static analyses is solving pointer analysis constraints. We present Pus, a highly efficient solver for inclusion-based pointer analysis. At the heart of Pus is a new constraint solving algorithm that significantly advances the state-of-the-art. Unlike the existing algorithms (i.e., wave and deep propagation) which construct a holistic constraint graph, at each stage Pus only considers partial constraints that causally affect the final fixed-point computation. In each iteration Pus extracts a small causality subgraph and it guarantees that only processing the causality subgraph is sufficient to reach the same global fixed point. Our extensive evaluation of Pus on a wide range of real-world large complex programs yields highly promising results. Pus is able to analyze millions of lines of code such as PostgreSQL in 10 minutes on a commodity laptop. On average, Pus is more than 7× faster in solving context-sensitive constraints, and more than 2× faster in solving context-insensitive constraints compared to the state of the art wave and deep propagation algorithms. Moreover, Pus has been used to find tens of previous unknown bugs in high-profile codebases including Linux, Redis, and Memcached.

We present OMPRACER, a static tool that uses flow-sensitive, interprocedural analysis to detect data races in OpenMP programs. OMPRACER is fast, scalable, has high code coverage, and supports the most common OpenMP features by combining state-of-the-art pointer analysis, novel value-flow analysis, happens-before tracking, and generalized modelling of OpenMP APIs. Unlike dynamic tools that currently dominate data race detection, OMPRACER achieves almost 100% code coverage using static analysis to detect a broader category of races without running the program or relying on specific input or runtime behaviour. OMPRACER has competitive precision with dynamic tools like Archer and ROMP: passing 105/116 cases in DataRaceBench with a total accuracy of 91%. OMPRACER has been used to analyze several Exascale Computing Project proxy applications containing over 2 million lines of code in under 10 minutes. OMPRACER has revealed previously unknown races in an ECP proxy app and a production simulation for COVID19.