In this paper, we propose a novel method for context-sensitive pointer analysis using the value flow graph (VFG) formulation. We achieve context-sensitivity by simultaneously applying function cloning and computing context-free language reachability (CFL-reachability) in a novel way. In contrast to existing clone-based and CFL-based approaches, flow-sensitivity is easily integrated in our approach by using a flow-sensitive VFG where each value flow edge is computed in a flow-sensitive manner. We apply context-sensitivity to both local variables and heap objects and propose a new approximation for heap cloning.

In this paper, we introduce Parfait, a static bug-checking tool for C/C++ applications. Parfait achieves precision and scalability at the same time by employing a layered program analysis framework. In Parfait, different analyses varying in precision and runtime expense can be invoked on demand to detect defects of a specific type, effectively achieving higher precision with smaller runtime overheads. Several production organizations within Oracle have started to integrate Parfait into their development process. Feedback from various production teams suggests that it is precise and scalable: the tool is able to analyze the OpenSolarisTM operating system and network consolidation (ON) with more than 6 million lines of code in 1 hour, and report thousands of defects with a false positive rate of close to 10%.

Points-to analysis is a fundamental static analysis technique which computes the set of memory objects that a pointer may point to. Many different applications, such as security-related program analyses, bug checking, and analyses of multi-threaded programs, require precise points-to information to be effective. Recent work has focused on improving the precision of points-to analysis through flow-sensitivity and great progress has been made. However, even with all recent progress, flow-sensitive points-to analysis can still be much slower than a flow-insensitive analysis.

Although buffer overflow detection has been studied for more than 20 years, it is still the most common source of security vulnerabilities in systems code. Different approaches using symbolic analysis have been proposed to detect this vulnerability. However, existing symbolic analysis techniques are either too complex to scale to millions of lines of code (MLOC), or too simple to effectively handle loops and complex program structures.

The goal of the Parfait project is to find bugs in C source code in a scalable and precise way. To this end, Parfait was designed as a framework with layers of sound program analyses, multiple layers per bug type, to identify bugs in a program more quickly and accurately.