Abstract: The present invention discloses a software reliability simulation analysis method based on virtual reality and a complex network, which realizes a two-layer network displaying the coupling of a task network and a function complex network in a virtual reality environment and is convenient for technicians to observe the operation of the network from multiple perspectives. On the basis of a technology of virtual reality, the present invention determines the task simulation based on an operation section, observes the flow of codes and the number of passing through function nodes in real time during the execution of a task, and calculates and assesses the importance degree of the nodes. The task simulation method based on the operation section is more convincing for the assessment of the importance of the nodes.

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 for establishing fault diagnosis technique based on contingent Bayesian networks, comprising steps of: step (1) determining a domain of an unknown object to be reasoned; step (2) defining a model structure by adopting a first-order logic language; step (3) generating a Blog model; step (4) transforming the Blog model into the contingent Bayesian networks; step (5) defining the contingent Bayesian networks; step (6) learning parameters of the contingent Bayesian networks; and step (7) reasoning a fault of the contingent Bayesian networks by utilizing a Markov chain Monte Carlo Method. By the steps mentioned above, establishing fault diagnosis technique based on contingent Bayesian networks is achieved.

Abstract: The present invention discloses a software reliability simulation analysis method based on virtual reality and a complex network, which realizes a two-layer network displaying the coupling of a task network and a function complex network in a virtual reality environment and is convenient for technicians to observe the operation of the network from multiple perspectives. On the basis of a technology of virtual reality, the present invention determines the task simulation based on an operation section, observes the flow of codes and the number of passing through function nodes in real time during the execution of a task, and calculates and assesses the importance degree of the nodes. The task simulation method based on the operation section is more convincing for the assessment of the importance of the nodes.

Abstract: A construction method of a software accelerated testing technology based on a noise resonance includes steps of: (1), collecting a source code of software to be tested; (2), automatically generating software test cases based on an intelligent evolving method, until information same or similar as a fault phenomenon is searched; (3), starting a saturation noise mode, and meanwhile exerting all controllable noise sources at a maximum intensity; (4), exerting all the controllable noise sources at a minimum intensity; (5), starting a strategy noise interference mode, and generating a noise resonance; (6), continuously exerting noises at a noise intensity able to generate the noise resonance; and (7), generating effective test sequences. Through the above steps, construction of the software accelerated testing technology based on the noise resonance is completed, which helps software testers accelerate recurrence of a software fault during testing and update the software to increase a reliability thereof.

Abstract: A method for degradation modeling and lifetime prediction considering recoverable shock damages includes steps of: Step 1: collecting degradation data; Step 2: establishing a degradation model; Step 3: estimating the parameters; and Step 4: predicting lifetime and reliability. Advantages and effects of the present invention are: A) The method of the present invention takes into account the conditions under which the shock damage can be partially or fully recovered, improving the prediction accuracy of lifetime and reliability of products meeting such conditions. B) The method of the present invention considers the shock effects on product performance, which considers the shock effects on both the degradation rate and the degradation signal, wherein prediction method is more realistic and prediction accuracy is improved. C) Many conventional degradation models are special cases when some of the parameters to be estimated in the model of the present invention are zero.

Abstract: A degradation modeling and lifetime prediction method considering effective shocks includes steps of: first collecting degradation test data, then establishing a performance degradation model, and determining an environment or load changing rate threshold of a product subjected to effective shock based on the test data; estimating parameters in the model, and determining effective shock occurrence times based on the future environmental or load profile, and finally preforming lifetime and reliability prediction. Specific steps are as follows: step 1: collecting degradation test data; step 2: establishing a degradation model; step 3: determining an environment or load changing rate threshold; step 4: estimating the parameters; step 5: predicting the times that effective shocks occur; and step 6: performing reliability prediction.

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 construction method of a software accelerated testing technology based on a noise resonance includes steps of: (1), collecting a source code of software to be tested; (2), automatically generating software test cases based on an intelligent evolving method, until information same or similar as a fault phenomenon is searched; (3), starting a saturation noise mode, and meanwhile exerting all controllable noise sources at a maximum intensity; (4), exerting all the controllable noise sources at a minimum intensity; (5), starting a strategy noise interference mode, and generating a noise resonance; (6), continuously exerting noises at a noise intensity able to generate the noise resonance; and (7), generating effective test sequences. Through the above steps, construction of the software accelerated testing technology based on the noise resonance is completed, which helps software testers accelerate recurrence of a software fault during testing and update the software to increase a reliability thereof.

Abstract: A method for establishing fault diagnosis technique based on contingent Bayesian networks, comprising steps of: step (1) determining a domain of an unknown object to be reasoned; step (2) defining a model structure by adopting a first-order logic language; step (3) generating a Blog model; step (4) transforming the Blog model into the contingent Bayesian networks; step (5) defining the contingent Bayesian networks; step (6) learning parameters of the contingent Bayesian networks; and step (7) reasoning a fault of the contingent Bayesian networks by utilizing a Markov chain Monte Carlo Method. By the steps mentioned above, establishing fault diagnosis technique based on contingent Bayesian networks is achieved.