The C Preprocessor (CPP) is the tool of choice for the implementation of variability in many large-scale configurable software projects. Linux, probably the most-configurable piece of software ever, employs more than 10,000 preprocessor variables for this purpose. However, this de-facto variability tends to be "hidden in the code"; which on the long term leads to variability defects, such as dead code or inconsistencies with respect to the intended (modeled) variability of the software. This calls for tool support for the efficient extraction of (and reasoning over) CPP-based variability.We suggest a novel approach to extract CPP-based variability. Our tool transforms CPP-based variability in O(n) complexity into a propositional formula that "mimics" all valid effects of conditional compilation and can be analyzed with standard SAT or BDD packages.Our evaluation results demonstrate the scalability and practicability of the approach. A dead-block-analysis on the complete Linux source tree takes less than 30 minutes; we thereby have revealed 60 dead blocks, 2 of which meanwhile have been confirmed as new (and long-lasting) bugs; the rest is still under investigation.

Nearly ten years after its first presentation and five years after its first application to operating systems, the suitability of AspectOriented Programming (AOP) for the development of operating system kernels is still highly in dispute. While the AOP advocacy emphasizes the benefits of AOP towards better configurability and maintainability of system software, most kernel developers express a sound skepticism regarding the thereby induced runtime and memory costs: Operating system kernels have to be lean and efficient. We have analyzed the runtime and memory costs of aspects in general, on the level of µ-benchmarks, and by refactoring and extending the eCos operating system kernel using AspectC++, an AOP extension to the C++ language. Our results show that most AOP features do not induce a intrinsic overhead and that the actual overhead induced by AspectC++ is very low. We have also analyzed a test case with significant aspect-related costs. This example shows how the structure of the underlying kernel can have a negative impact on aspect implementations and how these costs can be avoided by an aspect-aware design. Based on this analysis, our conclusion is that AOP is suitable for the development of operating system kernels and other kinds of highly efficient infrastructure software.