论文信息 - Inferring automata-based programs from specification with mutation-based ant colony optimization

Inferring automata-based programs from specification with mutation-based ant colony optimization

In this paper we address the problem of constructing correct-by-design programs with the use of the automata-based programming paradigm. A recent algorithm for learning finite-state machines (FSMs) MuACOsm is applied to the problem of inferring extended finite-state machine (EFSM) models from behavior examples (test scenarios) and temporal properties, and is shown to outperform the genetic algorithm (GA) used earlier.

Daniil Chivilikhin | Vladimir Ulyantsev

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