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| Content Provider | ACM Digital Library |
|---|---|
| Author | Gazzillo, Paul |
| Abstract | Feature-oriented software design is a useful paradigm for building and reasoning about highly-configurable software. By making variability explicit, feature-oriented tools and languages make program analysis tasks easier, such as bug-finding, maintenance, and more. But critical software, such as Linux, coreboot, and BusyBox rely instead on brittle tools, such as Makefiles, to encode variability, impeding variability-aware tool development. Summarizing Makefile behavior for all configurations is difficult, because Makefiles have unusual semantics, and exhaustive enumeration of all configurations is intractable in practice. Existing approaches use ad-hoc heuristics, missing much of the encoded variability in Makefiles. We present Kmax, a new static analysis algorithm and tool for Kbuild Makefiles. It is a family-based variability analysis algorithm, where paths are Boolean expressions of configuration options, called reaching configurations, and its abstract state enumerates string values for all configurations. Kmax localizes configuration explosion to the statement level, making precise analysis tractable. The implementation analyzes Makefiles from the Kbuild build system used by several low-level systems projects. Evaluation of Kmax on the Linux and BusyBox build systems shows it to be accurate, precise, and fast. It is the first tool to collect all source files and their configurations from Linux. Compared to previous approaches, Kmax is far more accurate and precise, performs with little overhead, and scales better. . |
| Starting Page | 279 |
| Ending Page | 290 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781450351058 |
| DOI | 10.1145/3106237.3106283 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2017-08-21 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Makefiles Configuration Kbuild Variability Static analysis Kmax |
| Content Type | Text |
| Resource Type | Article |
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