
The authors present a novel control-flow refinement (CFR) technique that can be used to improve the automated complexity analysis of probabilistic integer programs. They prove the soundness of their CFR approach and demonstrate its benefits by implementing it in their complexity analysis tool KoAT.


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control-flow-refinement-improves-complexity-analysis-of-probabilistic-programs-in-koat


Control-Flow Refinement Improves Complexity Analysis of Probabilistic Programs in KoAT


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The authors present a new method for static equivalence and similarity refutation analyses of probabilistic program pairs. The method is fully automated, applicable to infinite-state probabilistic programs, and provides formal guarantees on the correctness of its results.


automated-formal-analysis-of-equivalence-and-similarity-of-probabilistic-program-outputs


Automated Formal Analysis of Equivalence and Similarity of Probabilistic Program Outputs
