Research And Application Of IOS Application Credibility Test Based On Behavior Statement

With the advancement of technology,the mobile Internet industry has achieved rapid development.The mobile intelligent terminals mainly represented by iOS and Android operating systems have been rapidly developed and popularized on a global scale.On the iOS platform,there are more and more malware,harmful software and "inconsistent" software.Such software will bring huge economic losses to people,which seriously threatens people's personal and data security.Although Apple has launched App Store audits and other measures for these malicious and harmful software,it is generally believed that the iOS system is more secure than other systems,but there are security incidents such as XcodeGhost,YouMi SDK and other malicious stealing of user information.This shows that software that passes the App Store review process may also have security risks.Therefore,how to ensure the credibility of mobile terminal applications is a problem that needs to be solved at present.This article uses the iOS application as a research object to study how to test the credibility of the software.At the same time,due to the increasing size of software systems,traditional test methods need to occupy a large amount of time and resources in the software development cycle.Therefore,an efficient and fast testing technique is needed,so the automatic generation of test cases is also a problem to be solved in this paper.In recent years,research scholars at home and abroad have applied heuristic optimization algorithms such as genetic algorithm and simulated annealing algorithm in the research of automatic generation of test cases,which greatly improved the efficiency of software testing.Compared with most evolutionary optimization algorithms,particle swarm optimization has the characteristics of fast convergence,less adjustment parameters and strong versatility.However,in the practical application,the particle swarm optimization algorithm has problems such as lack of diversity of particles in the late stage of the algorithm,reduction of search precision and easy to fall into local optimal solution.Aiming at this,this paper proposes a particle swarm optimization algorithm based on dynamic adaptive and chaotic search.For the software testing process,this paper proposes a test method that combines software credibility with software test case automatic generation technology.First,the iOS system is analyzed,and the credible attribute is extracted in combination with the behavior declaration as the initial input value of the test case generation algorithm.Then,in the selection of the optimal algorithm,the improved particle swarm algorithm is used to complete the automatic generation of credible test cases.The final operation results show that the credible test case automatic generation system implemented in this paper can accelerate the software testing process while accurately verifying the software credibility.