研究目的
Investigating an external memory approach for finding all accepting cycles of large-scale systems.
研究成果
DAAC has better practical efficiency on the whole than DAC, MAP and IDDFS. It has important significance for debugging in large-scale system designs.
研究不足
The scales of the verified systems are to some extent limited because it exploits a minimal perfect hash function.
1:Experimental Design and Method Selection:
DAAC first searches for the accepting strongly connected components (ASCCs), and then finds all accepting cycles of every ASCC.
2:Sample Selection and Data Sources:
The automaton is treated as a directed graph that has an initial state s0 and an accepting state set F.
3:List of Experimental Equipment and Materials:
External memory devices (disks), minimal perfect hash function (MPHF).
4:Experimental Procedures and Operational Workflow:
DAAC traverses the accepting state set, searches for the ASCC containing the accepting state, and then finds accepting cycles of the ASCC.
5:Data Analysis Methods:
Complexity and experimental comparisons with the state-of-the-art algorithms.
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