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Highly-configurable systems written in C form our most critical computing infrastructure. The preprocessor is integral to C, because conditional compilation enables such systems to produce efficient object code. However, the preprocessor makes code harder to reason about for both humans and tools. Previous approaches to this challenge developed new program analyses for unpreprocessed source code or developed new languages and constructs to replace the preprocessor. But having specialpurpose analyses means maintaining a new toolchain, while new languages face adoption challenges and do not help with existing software. We propose the best of worlds: eliminate the preprocessor but preserve its benefits. Our design replaces preprocessor usage with C itself, augmented with syntax-preserving, backwards-compatible dependent types. We discuss automated conditional compilation to replicate preprocessor performance. Our approach opens new directions for research into new compiler optimizations, dependent types for configurable software, and automated translation away from preprocessor use.
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Static data-flow analysis for software product lines in C: Revoking the preprocessor’s special role
Abstract Many critical codebases are written in C, and most of them use preprocessor directives to encode variability, effectively encoding software product lines. These preprocessor directives, however, challenge any static code analysis. SPLlift, a previously presented approach for analyzing software product lines, is limited to Java programs that use a rather simple feature encoding and to analysis problems with a finite and ideally small domain. Other approaches that allow the analysis of real-world C software product lines use special-purpose analyses, preventing the reuse of existing analysis infrastructures and ignoring the progress made by the static analysis community. This work presents VarAlyzer , a novel static analysis approach for software product lines. VarAlyzer first transforms preprocessor constructs to plain C while preserving their variability and semantics. It then solves any given distributive analysis problem on transformed product lines in a variability-aware manner. VarAlyzer ’s analysis results are annotated with feature constraints that encode in which configurations each result holds. Our experiments with 95 compilation units of OpenSSL show that applying VarAlyzer enables one to conduct inter-procedural, flow-, field- and context-sensitive data-flow analyses on entire product lines for the first time, outperforming the product-based approach for highly-configurable systems.
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- PAR ID:
- 10390460
- Date Published:
- Journal Name:
- Automated Software Engineering
- Volume:
- 29
- Issue:
- 1
- ISSN:
- 0928-8910
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1007/s10515-022-00333-1
