A generalized JM model with applications to imperfect debugging in software reliability

作者：Chang Yen Chang; Liu Ching Ti^*

来源：Applied Mathematical Modelling, 2009, 33(9): 3578-3588.

DOI：10.1016/j.apm.2008.11.018

• Forecasting
• Gibbs sampling
• Prequential likelihood ratio
• Self-exciting point process
• Supermartingale

For their nice mathematical properties, state space models have been widely used, especially for forecasting. Over the last decades, the study of tracking software reliability by statistical models has attracted scientists' attention. However, most of models focus on perfect debugging although practically imperfect debugging arises everywhere. In this paper, a non-Gaussian state space model is modified to predict software failure time with imperfect debugging. In fact, this model is very flexible so that we can modify the system equation in this model to satisfy the various situations. Besides, this model is suitable for tracking software reliability, and applied to two well known datasets on software failures.

• 出版日期2009-9