Open AccessAutomatic generation of trusted test cases based on adaptive genetic algorithm
Author(s) -
Danyang Wu,
Lei Yu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1865/4/042074
Subject(s) - computer science , credibility , software , web application , genetic algorithm , consistency (knowledge bases) , field (mathematics) , convergence (economics) , the internet , software engineering , statement (logic) , data mining , algorithm , machine learning , artificial intelligence , operating system , mathematics , political science , pure mathematics , law , economics , economic growth
In recent years, the development and operating environment of software system has developed from the traditional closed and static environment to an open and dynamic Internet environment. The software system has become increasingly large and difficult to control, and the emergence of defects and loopholes is inevitable, resulting in the problem of software credibility [1]. How to improve the credibility of software has become the core hot issue in the field of software engineering [2]. In this paper, we will test the credibility of web applications based on the idea of “consistency of words and deeds”. By analyzing the characteristics of web applications, define the trusted behavior statement rules of web applications, and combine the genetic algorithm to realize the automatic generation of trusted test cases. Because the basic genetic algorithm has the shortcoming of “premature convergence”, in this paper, we will use adaptive parameters to implement genetic algorithm, and through the experimental verification, the adaptive parameter genetic algorithm can effectively improve the efficiency of searching the optimal solution.