Translation Validation of Optimizing Compilers
Candidate: Yi Fang
Advisor: Amir Pnueli and Lenore Zuck


There is a growing awareness, both in industry and academia, of the crucial role of formally verifying the translation from high-level source-code into low-level object code that is typically performed by an optimizing comiler. Formally verifying an optimizing compiler, as one woule verify any other large program, is not feasible due to its size, ongoing evolution and modification, and possibly, proprietary considerations. Translation validation is a novel approach that offers an alternative to the verification of translator in general and compilers in particular: Rather than verifying the compiler itself, one constructs a validation tool which, after every run of the compiler, formally confirms that the target code produced in the run is a correct translation of the source program. This thesis work takes an important step towards ensuring an extremely high level of confidence in compilers targeted at EPIC architectures.

In this thesis, we focus on the translation validation of structure preserving optimizations, i.e. transformations that do not modify programs' structure in a major way. This category of optimizations covers most of the global optimizations performed by compilers. This thesis has two main parts. One develops a proof rule that formally establishes the correctness of structure preserving transformation based on computational induction. The other part is the development of a tool that applies the proof rule to the automatic validation of global optimizaitons performed by Intel's ORC compiler for IA-64 architecture. With minimal instrumentation from the compiler, the tool constructs ''verification conditions'' -- formal theorems that, if valid, establish the correctness of a translation. The verificaiton conditions are then transferred to an automatic theorem prover that checks their validity. Together, the tool offers a fully automatic method to formally establish the correctness of each translation.