Method for automatically generating data flow test case based on particle swarm optimization algorithm

Abstract

The invention discloses a method for automatically generating a data flow test case based on a particle swarm optimization algorithm, which belongs to the field of software testing, and comprises the following steps of: firstly, improving the particle swarm optimization algorithm, namely designing a fitness function according to a branch distance, adjusting and updating an inertia weight factor of a particle speed, and simultaneously providing a chaos disturbance strategy; automatically generating a test case set based on data flow based on an improved particle swarm algorithm; the method specifically comprises the following steps of: obtaining a tested program, and performing data flow analysis on the tested program so as to obtain all definition-use pairs in the program; performing initialization by using a random algorithm in the improved particle swarm optimization; obtaining a fitness function according to a branch distance method; and generating a test case covering all definition-use pairs by using an improved particle swarm algorithm. According to the method, the improved particle swarm algorithm is applied to automatic generation of the test case oriented to the data flow, so that the generation efficiency and the coverage rate of the test case are improved, and the software testing efficiency is further improved.

Description

Technical field [0001] The present invention belongs to the field of software testing, and in particular to a data stream test case for a particle group algorithm based on automatic generation method. Background technique [0002] One of the difficulties of software testing automation is to perform automatic generation of test cases under the premise of meeting a certain coverage criterion. The test overlay is important as the important basis for judging testing. The main is: based on control flow test coverage criteria and data stream test Coverage guidelines. However, due to the control flow-based criteria, it is easy to miss the status-oriented state-oriented state dependencies, and the data stream can be obtained well, so the data stream-based test is a new research hotspot. [0003] In recent years, the use of the method of automatically generating the test case of the dollar heuristic algorithm with the data flow ratio, and this method has also improved significantly in imp...

AI Technical Summary

Problems solved by technology

Other meta-heuristic algorithms such as particle swarm optimization are also gradually applied to the automatic generation of test cases based on data flow, but the current automatic generation of test cases based on data flow has the following problems: First, in the data flow test criteria, the The test case information contained in the fitness function used cannot better guide the evolution of test cases

Second, it is difficult for the particle swarm algorithm used in the data flow test to converge to the global optimum, and it is easy to fall into the local optimum

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