The Design And Implementation Of Code Review Auxiliary Tool Based On Best Practices

Code quality is a key research topic in software engineering.Code review can help developers find the problems and defects of repositories in the early stage of software development,and reduce the later maintenance cost of software products effectively.Code review is considered to be one of the most effective code quality assurance activities and it is widely used in the open source community and industry today.Over the past decade,companies have been sharing best practices for code review based on their own experience,some of which have been noticed by academic researchers and improved accordingly.However,a number of best practices have not been systematically summarized in the existing literature.For the majority of code review practitioners,it is difficult to judge the value of many best practices according to their actual situation.Moreover,they lack of index measurement system to promote the continuous improvement of code review process,which eventually leads to a lot of costs,but the return is not up to expectations.The objective of this thesis is to apply the best practices reasonably to the actual code review scenarios,and improve the code review process through a thorough index measurement system,so as to give full play to the greater value of code review activities.Firstly,this thesis sorted out 37 code review best practices for further analysis through literature survey.Secondly,interviews and questionnaires were carried out in target enterprises to obtain 11 pain points in code review scenarios.Combined with pain points matching,23 code review best practices were selected.The design and implementation of code review auxiliary tool based on best practices was completed on the Git Lab platform of target enterprise by using Chrome extension.And a code review index measurement system was constructed using Delphi method to help code review practitioners better improve internal code review activities.The code review auxiliary tool based on best practices includes five modules: content detection module,decision aid module,work timing module,index display module and practices setting module.The content detection module detects all kinds of input information of code authors and reviewers through the algorithm model to ensure that the code review activities are active and efficient.By displaying decision information and data,the decision aid module helps code authors to choose the right reviewers and helps reviewers to plan the working time reasonably.The work timing module helps reviewers to control the work rhythm and improve the efficiency of review through timer and time consumption statistics.The index display module visualizes the data of the code review index measurement system to continuously discover the process bottlenecks and improvement points.The practices settings module configures the application of best practices capabilities.Finally,this thesis verified the code review auxiliary tool based on best practices with functional testing and non functional testing,and the results show the Chrome extension tool implemented in this thesis could apply the best practices to the code review process.In the future,this tool will be further improved from the aspects of function implementation and platform compatibility,thus better assist code review practitioners to apply code review best practices.