Blve: Should the Current Software Version Be Suitable for Release?

Recently, agile development has become a popular software development method and many version iterations occur during agile development. It is very important to ensure the quality of each software version. However in actual development, it is difficult to know every stage or version about large-scale software development. That means developers do not know exactly which version the current project corresponds to. Simultaneously, there are many necessary requirements for software release in actual development. When we know exactly the version corresponding to the current project, we can know whether the current software version meets the release requirements. Therefore, we need a good software version division method. This paper presents a novel software version division method Blve by using machine learning method. We construct an accurate division model trained with Support Vector Regression method (SVR) to divide software version by processing the data which is commonly recorded in bug list. Then, we process the results of the regression and use the classification indicators for evaluation. In addition, we propose a slope-based approach to optimize the model, and this optimization can improve the accuracy performance measure to about 95%.