This dissertation makes the case that programs can be updated while they run, with modest programmer effort, while providing certain update safety guarantees, and without imposing a significant performance overhead. Few systems are designed with on-the-fly updating in mind. Those systems that permit it support only a very limited class of updates, and generally provide no guarantees that following the update, the system will behave as intended. We tackle the on-the-fly updating problem using a compiler-based approach called dynamic software updating (DSU), in which a program is patched with new code and data while it runs. The challenge is in making DSU practical: it should support changes to programs as they occur in practice, yet be safe, easy to use, and not impose a large overhead. This dissertation makes both theoretical contributions—formalisms for reasoning about, and ensuring update safety—and practical contributions—Ginseng, a DSU implementation for C. Ginseng supports a broad range of changes to C programs, and performs a suite of safety analyses to ensure certain update safety

General-purpose operating systems, such as Linux, are increasingly being used in embedded systems. Computational resources are usually limited, and embedded processors often have a limited amount of memory. This makes code size especially important. This paper describes techniques for automatically reducing the memory footprint of general-purpose operating systems on embedded platforms. The problem is complicated by the fact that kernel code tends to be quite different from ordinary application code, including the presence of a significant amount of hand-written assembly code, multiple entry points, implicit control flow paths involving interrupt handlers, and frequent indirect control flow via function pointers. We use a novel “approximate decompilation” technique to apply source-level program analysis to hand-written assembly code. A prototype implementation of our ideas on an Intel x86 platform, applied to a Linux kernel that has been configured to exclude unnecessary code, obtains a code size reduction of close to 24%. 1.

There is increasing interest in using general-purpose operating systems, such as Linux, on embedded platforms. It is especially important in embedded systems to use memory efficiently because embedded processors often have limited physical memory. This paper describes an automatic technique for reducing the memory footprint of general-purpose operating systems on embedded platforms by keeping infrequently executed code on secondary storage and loading such code only if it is needed at run time. Our technique is based on an old idea—memory overlays—and it does not require hardware or operating system support for virtual memory. A prototype of the technique has been implemented for the Linux kernel. We evaluate our approach with two benchmark suites: MiBench and MediaBench, and a Web server application. The experimental results show that our approach reduces memory requirements for the Linux kernel code by about 53 % with little degradation in performance.