Engineering a static verification tool for GPU kernels

We report on practical experiences over the last 2.5 years related to the engineering of GPUVerify, a static verification tool for OpenCL and CUDA GPU kernels, plotting the progress of GPUVerify from a prototype to a fully functional and relatively efficient analysis tool. Our hope is that this experience report will serve the verification community by helping to inform future tooling efforts. © 2014 Springer International Publishing

Making Software Verification Tools Really Work

We discuss problems and barriers which stand in the way of producing verification tools that are robust, scalable and integrated in the software development cycle. Our analysis is that these barriers span a spectrum from theoretical, through practical and even logistical issues. Theoretical issues are the inherent complexity of program verification and the absence of a common, accepted semantic model in tools. Practical hurdles include the challenges arising from real-world systems features, such as floating-point arithmetic and weak memory. Logistical obstacles we identify are the lack of standard benchmarks to drive tool quality and efficiency, and the difficulty for academic research institutions of allocating resources to tool development. We propose simple measures which we, as a community, could adopt to make the design of serious verification tools easier and more credible. Our long-term vision is for the community to produce tools that are indispensable for a developer but so seamlessly integrated into a development environment, as to be invisible