The Efficiency Evaluation Of GitHub Developers Based On Improved DEA Model

The efficiency evaluation of GitHub developer is extremely concerned by IT companies.However,GitHub itself can not see the relative efficiency of developers,which has a great impact on the talent selection of IT company.The traditional developer efficiency evaluation is only a contrived estimate of the developer's data based on the GitHub data,which is neither accurate nor a waste of time looking at the developer's data on the GitHub.In this paper,we use data envelopment analysis to solve the problem of IT company,which can solve the relative efficiency between developers.Then,we ameliorate the original DEA model to deal with developer data on GitHub,which is compared the relative efficiency of GitHub developers.Traditional DEA models can only handle the incoming and output data of exact numbers,it can't deal with data containing fuzziness.In this paper,the concept of fuzzy number is introduced on the basis of traditional DEA,a new fuzzy DEA model and a fuzzy DEA model based on cut set are formed.Then,then conditions and advantages and disadvantages of the two models have been studied.Finally,the fuzzy DEA model based on the cut set is the most suitable method to process the data of the developers and sort the efficiency of the developers.Finally,this paper designs a GitHub developer efficiency evaluation system,which obtains data from GitHub,processes data by improved DEA model,and finally shows the efficiency evaluation of developers intuitively.This system not only solves the problem of efficiency evaluation of developers,but also improves the accuracy of manual evaluation.I believe that the advent of this system is of great help to company and has a great prospect in the market.