The pull request mechanism is widely used for integrating developers' code in github,so that developers can make contribution for open source projects.The code review of pull request is an essential method to maintain the high quality of code in github.Assigning appropriate reviewers for a newly coming pull request can effectively reduce the delay between the submission of a pull request and the actual review of it.At present,the pull request is assigned manually by core developers in the project.To reduce this cost,we propose a reviewer recommender system based on information retrieval.This method can automatically recommend highly relevant reviewers for a newly coming pull request.Our method has also taken the impact factor and time decaying factor into consideration,and has received good performance that the top 1 precision can reach 68% and top 10 recall rate can reach 78%.