{"id":353,"date":"2018-11-06T00:57:02","date_gmt":"2018-11-06T00:57:02","guid":{"rendered":"http:\/\/se.kaist.ac.kr\/starlab\/?page_id=353"},"modified":"2018-12-12T10:56:39","modified_gmt":"2018-12-12T10:56:39","slug":"sos-simulation-model-slicer","status":"publish","type":"page","link":"https:\/\/se.kaist.ac.kr\/starlab\/tools-and-artifacts\/opensource-tools\/sos-simulation-model-slicer\/","title":{"rendered":"SoS Simulation Model Slicer"},"content":{"rendered":"

Background<\/strong><\/h4>\n

The SoS Simulation Model Slicer tool is a tool for slicing a simulation model based on the given statistical verification property. As described earlier in SoS target model slicing, the statistical model verification statistically obtains the verification results from the simulation results obtained by simulating the model several times. The larger the model, the more expensive it is to perform the simulation and the longer it takes to obtain the verification results.<\/p>\n

In order to overcome this, the SoS minimum verification target model calculation tool performs dynamic backward slicing from the statements related to the verification property to the SoS simulation model and makes it a feasible model. The result of the dynamic reverse slicing operation outputs a statement related to the verification property in the simulation model. After making the output results into an executable model, you can get a sliced \u200b\u200bSoS simulation model. The sliced \u200b\u200bSoS simulation model can improve the temporal efficiency by increasing the simulation speed, and the size of the SoS simulation model itself is also reduced, so it does not consume a lot of memory and can improve the spatial efficiency. In order to obtain such advantages, we implement the SoS minimum verification target model calculation tool in this study and verify that the SoS model can be calculated by extracting the statements related to the verification attributes accurately.<\/p>\n

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Tool Overview<\/strong><\/h4>\n