Much system software can be configured at compile time to tailor it with respect to a broad range of supported hardware architectures and application domains. A good example is the Linux kernel, which provides more than 10,000 configurable features, growing rapidly.From the maintenance point of view, compile-time configurability imposes big challenges. The configuration model (the selectable features and their constraints as presented to the user) and the configurability that is actually implemented in the code have to be kept in sync, which, if performed manually, is a tedious and error-prone task. In the case of Linux, this has led to numerous defects in the source code, many of which are actual bugs.We suggest an approach to automatically check for configurability-related implementation defects in large-scale configurable system software. The configurability is extracted from its various implementation sources and examined for inconsistencies, which manifest in seemingly conditional code that is in fact unconditional. We evaluate our approach with the latest version of Linux, for which our tool detects 1,776 configurability defects, which manifest as dead/superfluous source code and bugs. Our findings have led to numerous source-code improvements and bug fixes in Linux: 123 patches (49 merged) fix 364 defects,
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.
Recent advances in animal tracking technology have ushered in a new era in biologging. However, the considerable size of many sophisticated biologging devices restricts their application to larger animals, whereas older techniques often still represent the state-of-theart for studying small vertebrates. In industrial applications, low-power wireless sensor networks (WSNs) fulfill requirements similar to those needed to monitor animal behavior at high resolution and at low tag mass. We developed a wireless biologging network (WBN), which enables simultaneous direct proximity sensing, high-resolution tracking, and long-range remote data download at tag masses of 1 to 2 g. Deployments to study wild bats created social networks and flight trajectories of unprecedented quality. Our developments highlight the vast capabilities of WBNs and their potential to close an important gap in biologging: fully automated tracking and proximity sensing of small animals, even in closed habitats, at high spatial and temporal resolution.
With more than 11,000 optional and alternative features, the Linux kernel is a highly configurable piece of software. Linux is generally perceived as a textbook example for preprocessor-based product derivation, but more than 65 percent of all features are actually handled by the build system. Hence, variability-aware static analysis tools have to take the build system into account.However, extracting variability information from the build system is difficult due to the declarative and turing-complete MAKE language. Existing approaches based on text processing do not cover this challenges and tend to be tailored to a specific Linux version and architecture. This renders them practically unusable as a basis for variability-aware tool support -Linux is a moving target! We describe a robust approach for extracting implementation variability from the Linux build system. Instead of extracting the variability information by a text-based analysis of all build scripts, our approach exploits the build system itself to produce this information. As our results show, our approach is robust and works for all versions and architectures from the (git-)history of Linux.
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