Static Data-Flow Analysis for Software Product Lines in C (bibtex)
  author    = {Schubert, Philipp Dominik
               and Gazzillo, Paul
               and Patterson, Zach
               and Braha, Julian
               and Schiebel, Fabian
               and Hermann, Ben
               and Wei, Shiyi
               and Bodden, Eric},
  title     = {Static Data-Flow Analysis for Software Product Lines in C},
  subtitle  = {Revoking the Preprocessor's Special Role},
  journal   = {Automated Software Engineering},
  publisher = {Springer International Publishing},
  year      = {2022},
  numpages  = {35},
  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.},
  doi       = {10.1007/s10515-022-00333-1},
  url = {},
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