Improving the Productivity of Compiler Code Quality Analysis

Producing quality code is one of the most important goals of an optimizing compiler. Analyzing code quality is therefore an essential activity in compiler engineering. By motivating new optimizations and diagnosing regressions, it takes a bottleneck position in the process. However, it has been highly empirical, and dependent on architectures and tools. This makes it a difficult and time-consuming task, and its productivity is unpredictable and usually low. This paper proposes two novel approaches for code quality analysis. The first ap-proach focuses on the key scenario in compiler construction, the computation-intensive benchmarks. We observed that the workload upon the processor dominates the execu-tion time of such benchmarks. Therefore, we use the compiler to parse the workload. By doing this, the compiler applies its static analysis power to identify its own code quality issues and potentials. We have implemented a software system for this ap-proach and integrated it with our daily testing infrastructure. It automates the code quality analysis for Spec benchmarks, and provides developers relevant information i