{"id":165785,"date":"2014-01-01T00:00:00","date_gmt":"2014-01-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/minimization-of-symbolic-automata-2\/"},"modified":"2018-10-16T20:01:29","modified_gmt":"2018-10-17T03:01:29","slug":"minimization-of-symbolic-automata-2","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/minimization-of-symbolic-automata-2\/","title":{"rendered":"Minimization of Symbolic Automata"},"content":{"rendered":"
\n

Symbolic Automata extend classical automata by using symbolic alphabets instead of finite ones. Most of the classical automata algorithms rely on the alphabet being finite, and generalizing them to the symbolic setting is not a trivial task. In this paper we study the problem of minimizing symbolic automata. We formally define and prove the basic properties of minimality in the symbolic setting, and lift classical minimization algorithms (Huffman-Moore\u2019s and Hopcroft\u2019s algorithms) to symbolic automata. While Hopcroft\u2019s algorithm is the fastest known algorithm for DFA minimization, we show how, in the presence of symbolic alphabets, it can incur an exponential blowup. To address this issue, we introduce a new algorithm that fully benefits from the symbolic representation of the alphabet and does not suffer from the exponential blowup. We provide comprehensive performance evaluation of all the algorithms over large benchmarks and against existing state-of-the-art implementations. The experiments show how the new symbolic algorithm is faster than previous implementations.<\/p>\n<\/div>\n

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Symbolic Automata extend classical automata by using symbolic alphabets instead of finite ones. Most of the classical automata algorithms rely on the alphabet being finite, and generalizing them to the symbolic setting is not a trivial task. In this paper we study the problem of minimizing symbolic automata. We formally define and prove the basic 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