The Design And Implementation Of Automatic Generation System For Bug Report Of Mobile Application

As mobile application development cycle is getting shorter and shorter,applica-tion quality assurance requires more efficient testing methods.Compared with tradi-tional manual testing,automated testing methods have the advantages of high speed,repeatability,and multi-device batch execution,which can effectively improve testing efficiency.However,the logs generated by automated testing have low readability and often require manual review to locate bugs.Due to time constraints,it is difficult to ful-ly mine the bug information of multiple logs by manual analysis and lack of complete bug context,which results in developers unable to locate and fix bugs quickly.This thesis designs and implements an automatic generation system for bug re-port of mobile applications to solve the problems of low readability of logs and low efficiency of bug location in automated testing.By mining multiple logs generated by automated testing,this system builds a bug model containing complete context infor-mation,including operation sequence,stack information,bug screenshots,etc.The classification and deduplication of bugs are performed using classification algorithms(Decision Trees,Naive Bayes,etc.).The system recommends a fix for each bug for developers to refer to.Bug data is visualized by front-end pages to generate highly readable and instructive bug reports.The system implements the microservices archi-tecture based on the Dubbo framework,and the microservices interact through remote procedure calls,using Zookeeper as the service registration and discovery center.The system server is developed based on the Spring Boot framework.The front end is developed based on the Angular framework,and the front and back ends are load bal-anced by Nginx.The system uses MongoDB as a database for data persistence,Redis for data caching,and Docker to package services as images for rapid deployment and continuous integration using Jenkins.The system has deployed and stably supported the bug report generation function of the automated testing platform.The system's availability assessment experiment selected 8 open source mobile applications to perform automated testing on 20 mobile devices and generate bug reports.The experimental results have been manually veri-fied,and the average accuracy of bug reports reaches 93%.The system eliminates the need for developers to directly face the massive logs generated by automated testing tools and improves the efficiency of bug analysis by presenting complete bug context information.