Metamorphic testing is an effective way to alleviate the problems of testing Oracle, for which metamorphic relations are key. Studies have shown that the complexity of metamorphic expressions is related to their error detection capability. Therefore, an effective method for calculating the complexity of metamorphic relations can improve the efficiency of metamorphic testing to a certain extent. To address this issue, we analyse the types of input and output components of metamorphic relations described by expressions used in numerical computation programs, define the complexity of metamorphic relations according to the scale complexity in the classification of complexity concepts, and give a method for calculating the complexity of metamorphic relations. The experiments show that the complexity of the metamorphic relationship derived from the metamorphic relationship complexity calculation method is roughly positively correlated with its error detection capability. The complexity of the metamorphic relationship can provide a reference for the selection of metamorphic relationships.
Test cases are the key to software testing, and it is particularly important to generate and select test cases that detect faults more quickly. This paper first analyses the characteristics and applicability of typical ART, then combines the isolation forest algorithm with ART, proposes a test case generation technique for IForest-ART, and compares the fault detection effects of typical distance-based ART and IForest-ART in low to high dimensions. The experimental results show that the test validity of IForest-ART in high-dimensional input domain space is significantly higher than that of FSCS-ART, which effectively alleviates the problem of decreasing test validity of typical ART in high-dimensional input domain space and provides a new idea for ART.
The metamorphic test is a method to alleviate the unexpected value of the Oracle problem. The key point is the identification of the metamorphic relations. The identification of the metamorphic relations of scientific calculation programs is also a complex problem, and the likely of the metamorphic relation of the program can provide enlightening information for the identification of the metamorphic relations. The likely metamorphic relation can be regarded as the implicit expression of the input pattern and output pattern. This paper proposes an output pattern recognition technology based on the likely metamorphic relations of GEP. The technology is mainly aimed at the core neutron diffusion calculation program. The input pattern of the program, and then generate input data and run the program. Finally, in the corresponding output data results, through GEP data mining technology, the output pattern expressed in a variety of functional forms is obtained, which is further compared with analytical solutions and verified to be reliable likely metamorphic relations.
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