Hoisting C Structures Into Clay In Device Drivers

This project addresses the unreliability of operating system code, in particular in device drivers. Device driver software is the interface between the operating system and the device's hardware. Device drivers are written in low level code, making them difficult to understand. Almost all device drivers are written in the programming language C which allows for direct manipulation of memory. Due to the complexity of manual movement of data, most mistakes in operating systems occur in device driver code. The programming language Clay can be used to check device driver code at compile-time. Clay does most of its error checking statically to minimize the overhead of run-time checks in order to stay competitive with C's performance time. The Clay compiler can detect a lot more types of errors than the C compiler like buffer overflows, kernel stack overflows, NULL pointer uses, freed memory uses, and aliasing errors. Clay code that successfully compiles is guaranteed to run without failing on errors that Clay can detect. Even though C is unsafe, currently most device drivers are written in it. Not only are device drivers the part of the operating system most likely to fail, they also are the largest part of the operating system. As rewriting every existing device driver in Clay by hand would be impractical, this thesis is part of a project to automate translation of existing drivers from C to Clay. Although C and Clay both allow low level manipulation of data and fill the same niche for developing low level code, they have different syntax, type systems, and paradigms. This paper explores how C can be translated into Clay. It identifies what part of C device drivers cannot be translated into Clay and what information drivers in Clay will require that C cannot provide. It also explains how these translations will occur by explaining how each C structure is represented in the compiler and how these structures are changed to represent a Clay structure.

Sensitivity Gains, Linearity, and Spectral Reproducibility in Nonuniformly Sampled Multidimensional MAS NMR Spectra of High Dynamic Range

Recently, we have demonstrated that considerable inherent sensitivity gains are attained in MAS NMR spectra acquired by nonuniform sampling (NUS) and introduced maximum entropy interpolation (MINT) processing that assures the linearity of transformation between the time and frequency domains. In this report, we examine the utility of the NUS/MINT approach in multidimensional datasets possessing high dynamic range, such as homonuclear C-13-C-13 correlation spectra. We demonstrate on model compounds and on 1-73-(U-C-13,N-15)/74-108-(U-N-15) E. coli thioredoxin reassembly, that with appropriately constructed 50 % NUS schedules inherent sensitivity gains of 1.7-2.1-fold are readily reached in such datasets. We show that both linearity and line width are retained under these experimental conditions throughout the entire dynamic range of the signals. Furthermore, we demonstrate that the reproducibility of the peak intensities is excellent in the NUS/MINT approach when experiments are repeated multiple times and identical experimental and processing conditions are employed. Finally, we discuss the principles for design and implementation of random exponentially biased NUS sampling schedules for homonuclear C-13-C-13 MAS correlation experiments that yield high-quality artifact-free datasets.