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   	<dc:title>SuperDP: Differential privacy refutation via supermartingales</dc:title>
   	<dc:creator>Chatterjee, Krishnendu ; https://orcid.org/0000-0002-4561-241X</dc:creator>
   	<dc:creator>Kafshdar Goharshadi, Ehsan ; https://orcid.org/0000-0002-8595-0587</dc:creator>
   	<dc:creator>Zikelic, Dorde ; https://orcid.org/0000-0002-4681-1699</dc:creator>
   	<dc:subject>Static Program Analysis</dc:subject>
   	<dc:subject>Differential Privacy</dc:subject>
   	<dc:subject>Probabilistic Programming</dc:subject>
   	<dc:subject>Martingales</dc:subject>
   	<dc:subject>ddc:000</dc:subject>
   	<dc:description>Differential privacy (DP) has established itself as one of the standards for ensuring privacy of individual data. However, reasoning about DP is a challenging and error-prone task, hence methods for formal verification and refutation of DP properties have received significant interest in recent years. In this work, we present a novel method for automated formal refutation of є-DP. Our method refutes є-DP by searching for a pair of inputs together with a non-negative function over outputs whose expected value on these two inputs differs by a significant amount. The two inputs and the non-negative function over outputs are computed simultaneously, by utilizing upper expectation supermartingales and lower expectation submartingales from probabilistic program analysis, which we leverage to introduce a sound and complete proof rule for є-DP refutation. To the best of our knowledge, our method is the first method for є-DP refutation to offer the following four desirable features: (1) it is fully automated, (2) it is applicable to stochastic mechanisms with sampling instructions from both discrete and continuous distributions, (3) it provides soundness guarantees, and (4) it provides semi-completeness guarantees. Our experiments show that our prototype tool SuperDP achieves superior performance compared to the state of the art and manages to refute є-DP for a number of challenging examples collected from the literature, including ones that were out of the reach of prior methods.</dc:description>
   	<dc:publisher>Association for Computing Machinery</dc:publisher>
   	<dc:date>2026</dc:date>
   	<dc:type>info:eu-repo/semantics/article</dc:type>
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   	<dc:type>text</dc:type>
   	<dc:type>http://purl.org/coar/resource_type/c_2df8fbb1</dc:type>
   	<dc:identifier>https://research-explorer.ista.ac.at/record/22102</dc:identifier>
   	<dc:identifier>https://research-explorer.ista.ac.at/download/22102/22135</dc:identifier>
   	<dc:source>Chatterjee K, Goharshady E, Zikelic D. SuperDP: Differential privacy refutation via supermartingales. &lt;i&gt;Proceedings of the ACM on Programming Languages&lt;/i&gt;. 2026;10(PLDI). doi:&lt;a href=&quot;https://doi.org/10.1145/3808296&quot;&gt;10.1145/3808296&lt;/a&gt;</dc:source>
   	<dc:language>eng</dc:language>
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   	<dc:relation>info:eu-repo/semantics/altIdentifier/e-issn/2475-1421</dc:relation>
   	<dc:relation>info:eu-repo/semantics/altIdentifier/arxiv/2603.26215</dc:relation>
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