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<oembed><version>1.0</version><provider_name>Microsoft Research</provider_name><provider_url>https://www.microsoft.com/en-us/research</provider_url><author_name>Margus Veanes</author_name><author_url>https://www.microsoft.com/en-us/research/people/margus/</author_url><title>Symbolic Automata: The Toolkit - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="yTcOrXrOHJ"&gt;&lt;a href="https://www.microsoft.com/en-us/research/publication/symbolic-automata-the-toolkit/"&gt;Symbolic Automata: The Toolkit&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/symbolic-automata-the-toolkit/embed/#?secret=yTcOrXrOHJ" width="600" height="338" title="&#x201C;Symbolic Automata: The Toolkit&#x201D; &#x2014; Microsoft Research" data-secret="yTcOrXrOHJ" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><description>The symbolic automata toolkit lifts classical automata analysis to work modulo rich alphabet theories. It uses the power of state-of-the-art constraint solvers for automata analysis that is both expressive and efficient, even for automata over large finite alphabets. The toolkit supports analysis of finite symbolic automata and transducers over strings. It also handles transducers with [&hellip;]</description></oembed>
