Abstract: A construction method of a test case constraint control technology based on epigenetics includes steps of: 1: defining a fitness function, a genetic coding method, and a constraint control rule; 2: initializing parameters: setting a population size, an evolution number, and a termination fitness function value; 3: initializing a population: randomly generating an initial population; 4: performing evolution termination judgment; 5. performing constraint regulation based on the epigenetics: performing constraint methylation and constraint acetylation according to the constraint control rule; 6: selecting individuals; 7: completing epigenetic evolution of the population; and 8: outputting a test case set; wherein through the above steps, construction of an epigenetic test case constraint control technology is completed, so as to design test cases that are more in line with the actual operation conditions of the software, find more potential software failures, and improve the quality of software testing.

Abstract: A method and a system of identifying and estimating a complex analog circuit failure, belonging to the field of power electronic circuit failure prediction. The method includes the following steps: building a degradation simulation model of an analog circuit to be diagnosed, performing a parameter aging simulation experiment on different devices; extracting a time domain feature of each of output signals by using a time-series transformation method, building a health index of each of the devices based on angle similarity; identifying whether the analog circuit to be diagnosed is degraded and a starting point of degradation by combining a time moving window and a convolutional neural network; multiplexing part of hidden layers of the convolutional neural network and a long short term memory-recurrent neural network to estimate a health state of a degraded analog circuit; and evaluating prediction accuracy.

Abstract: A construction method of a test case constraint control technology based on epigenetics includes steps of: 1: defining a fitness function, a genetic coding method, and a constraint control rule; 2: initializing parameters: setting a population size, an evolution number, and a termination fitness function value; 3: initializing a population: randomly generating an initial population; 4: performing evolution termination judgment; 5. performing constraint regulation based on the epigenetics: performing constraint methylation and constraint acetylation according to the constraint control rule; 6: selecting individuals; 7: completing epigenetic evolution of the population; and 8: outputting a test case set; wherein through the above steps, construction of an epigenetic test case constraint control technology is completed, so as to design test cases that are more in line with the actual operation conditions of the software, find more potential software failures, and improve the quality of software testing.