Probability finite-state machine variation test case generation method

Abstract

The invention discloses a probability finite state machine variation test case generation method, which comprises the steps of defining a PFSM original state machine, and obtaining a test case set ofthe PFSM original state machine; defining a plurality of mutation operations and corresponding variants; wherein the mutation operation at least comprises probability change and migration target statechange; selecting test cases capable of killing strain allogeneities from the test case set of the PFSM original state machine by utilizing a hypothesis testing method, and generating a new test caseset for killing variants. The test case obtained by the method provided by the invention can effectively kill the variants, and the variation sufficiency is high; Meanwhile, whether each variant is equivalent to the original PFSM or not does not need to be judged, so that the test time is short.

Description

technical field [0001] The invention relates to the technical field of software testing, and more specifically, the invention relates to a method for generating a variation test case of a probabilistic finite state machine. Background technique [0002] Finite state machine is a formal specification description tool for describing software requirements, which has the advantages of accuracy, derivability and verifiability. Therefore, testing based on finite state machines, especially its test case generation technology, has been extensively studied [0003] . Domestic scholars have also carried out in-depth research on this aspect, Zhang Yong [2] proposed an improved method of Wp method, using this method can generate a relatively small number of test input sequences when the number of finite machine states is large. As a defect-oriented software testing technique, mutation testing has been widely used [3] . [0004] Probabilistic finite state machines are a generalizati...

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Problems solved by technology

The shortcomings of this method are: (1) Due to the huge number of PFSM variants, it is time-consuming to solve the test sequence after determining whether each variant is equivalent to the original PFSM one by one; (2) It cannot be determined by the output sequence of the test The cause and location of the variant

In addition, the literature [16, 17] did not provide methods for generating other variant test cases such as migration loss, changing input and changing output, and did not provide relevant auxiliary testing tools to verify the correctness and accuracy of the proposed method through experiments. effectiveness

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