Jieming Chi, Kiyoshi Honda, Hironori Washizaki, Yoshiaki Fukazawa, Kazuki Munakata, Sumie Morita, Tadahiro Uehara, and Rieko Yamamoto, “Defect Analysis and Prediction by Applying the Multistage Software Reliability Growth Model,” The 8th IEEE International Workshop on Empirical Software Engineering in Practice (IWESEP), pp.1-5, Tokyo, March 13, 2017. (to appear) (acceptance rate 9/18=50%)
In software development, defects are inevitable. To improve reliability, software reliability growth models are useful to analyze projects. Selecting an expedient model can also help with defect predictions, but the model must be well fitted to all the original data. A particular software reliability growth model may not fit all the data well. To overcome this issue, herein we use multistage modeling to fit defect data. In the multistage model, an evaluation is used to divide the data into several parts. Each part is fitted with its own growth model, and the separate models are recombined. As a case study, projects provided by a Japanese enterprise are analyzed by both traditional software reliability growth models and the multistage model. The multistage model has a better performance for data with a poor fit using a traditional software reliability growth model.