| As the largest open source community in the world today,GitHub provides tools about code quality checking,project continuous integration,and schedule management for developers in its MarketPlace.But there is still no effective tools to help developers in fixing bug.For software developers,fixing bug is a time-consuming and laborious task.And bug localization is an important part of this process.Using tools to predicting buggy source code files can help developers locate bug and improve efficiency in fixing bug.This paper designs and implements a bug localization system for the GitHub open source community.The system adopts the B/S architecture.The web page is built with Vue.js framework and iView component library.The browser side communicates with the server side through axios library.We defined communication interface based on RESTful API.To implement business logic,the server side is built with Spring Boot framework.At the same time,it integrated with components such as MyBatis for ORM mapping,log4j for recording operation logs and etc.For data persistence layer,we use Mysql to store the information.The system implements and integrates three IR-based bug localization technologies named BugLocator,BLUiR+,and AmaLgam+.It extracts information from source code files using the Abstract Syntax Tree.And then put this information together with bug reports.Bug localization technologies use them to calculate scores for each source code file.Finally,developers could check buggy source code files according to the results.This paper selects a total 1243 bug reports created before October 16,2018 about the open source project Zookeeper to verify the bug location accuracy of this system initially.The hit rate of Top1 in the bug localization result is 52.55%,the hit rate of Top 5 is 78.94%,and the hit rate of Top 10 is 87.45%.In addition,we simulated 500 users concurrently accessing 7 common interfaces in the system performance test.The results show that the average response time of the seven interfaces is 247ms,the highest is 447ms.All responses take less than 500ms and the error rate is 0.It meets the performance requirements used by small-scale developer groups. |
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