Efficient testing model based on Pareto distribution

Regression testing is a very important part of the program development cycle as it should be executed after feature is integrated or bugs are fixed each time. There are hundreds of test cases in the case library for a little complex product, it is impossible to perform all of the test cases in regression testing every time. Test engineers always select the regression cases by their experience only, most of the cases are executed for several times but cannot find any issues, and many of the defects are escaped from test engineers because of the existing cases have not been selected to run. Pareto distribution model is introduced to assist test engineers in selecting efficient regression cases those are expected to find most of the defects at the incipient stage of testing according to quantitative efficiency of the test cases. And this model helps test engineers to forecast the progress of fault finding also.