Apron: a library of numerical abstract domains for static analysis. This article describes Apron, a freely available library dedicated to the static analysis of the numerical variables of programs by abstract interpretation. Its goal is threefold: provide analysis implementers with ready-to-use numerical abstractions under a unified API, encourage the research in numerical abstract domains by providing a platform for integration and comparison, and provide teaching and demonstration tools to disseminate knowledge on abstract interpretation.

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  1. Abbasi, Rosa; Schiffl, Jonas; Darulova, Eva; Ulbrich, Mattias; Ahrendt, Wolfgang: Deductive verification of floating-point Java programs in KeY (2021)
  2. Meyer, Fabian; Hark, Marcel; Giesl, Jürgen: Inferring expected runtimes of probabilistic integer programs using expected sizes (2021)
  3. Sotoudeh, Matthew; Thakur, Aditya V.: SyReNN: a tool for analyzing deep neural networks (2021)
  4. Becchi, Anna; Zaffanella, Enea: PPLite: zero-overhead encoding of NNC polyhedra (2020)
  5. Chawdhary, Aziem; Robbins, Ed; King, Andy: Incrementally closing octagons (2019)
  6. Dimovski, Aleksandar S.; Brabrand, Claus; Wąsowski, Andrzej: Finding suitable variability abstractions for lifted analysis (2019)
  7. Howe, Jacob M.; King, Andy; Simon, Axel: Incremental closure for systems of two variables per inequality (2019)
  8. Ouadjaout, Abdelraouf; Miné, Antoine: Quantitative static analysis of communication protocols using abstract Markov chains (2019)
  9. Zolotykh, Nikolai Yu.; Bastrakov, Sergei I.: Two variations of graph test in double description method (2019)
  10. Amato, Gianluca; Rubino, Marco: Experimental evaluation of numerical domains for inferring ranges (2018)
  11. Boutonnet, Rémy; Halbwachs, Nicolas: Improving the results of program analysis by abstract interpretation beyond the decreasing sequence (2018)
  12. Heo, Kihong; Oh, Hakjoo; Yang, Hongseok: Learning analysis strategies for Octagon and context sensitivity from labeled data generated by static analyses (2018)
  13. Zaffanella, Enea: On the efficiency of convex polyhedra (2018)
  14. Botbol, Vincent; Chailloux, Emmanuel; Le Gall, Tristan: Static analysis of communicating processes using symbolic transducers (2017)
  15. Dan, Andrei; Meshman, Yuri; Vechev, Martin; Yahav, Eran: Effective abstractions for verification under relaxed memory models (2017)
  16. Jiang, Jiahong; Chen, Liqian; Wu, Xueguang; Wang, Ji: Block-wise abstract interpretation by combining abstract domains with SMT (2017)
  17. Liu, Jiangchao; Rival, Xavier: An array content static analysis based on non-contiguous partitions (2017)
  18. Magron, Victor; Constantinides, George; Donaldson, Alastair: Certified roundoff error bounds using semidefinite programming (2017)
  19. Maréchal, Alexandre; Monniaux, David; Périn, Michaël: Scalable minimizing-operators on polyhedra via parametric linear programming (2017)
  20. Maréchal, Alexandre; Périn, Michaël: Efficient elimination of redundancies in polyhedra by raytracing (2017)

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