中文摘要：

软件可靠性增长模型中测试阶段和操作运行阶段环境的不同导致了两个阶段故障检测率的不同．在随机过程类非齐次泊松过程（NHPP）中的经典模型G—O模型基础上，考虑运行剖面和测试剖面的不同，对测试阶段和操作运行阶段的故障检测率进行了转化，得到了较好的刻画测试阶段和操作阶段失效率差别的模型（TO—SRGM）．最后，通过实例用最小二乘法对此模型的参数进行了估计．实验结果表明，在某些失效数据集上TO—SRGM的拟和效果比G—O模型和PZ—SRGM好．

英文摘要：

The testing and operation environment may be essentially different, and thus the fault detection rate of testing is different from that of the operation phase. Based on the G-O model, the representative of non-homogeneous Poisson process （NHPP）, the fault detection rate from testing to operation is transformed considering the differences of profile of these two phases, and then a more precise NHPP model （TO- SRGM） considering the differences of fault intensity of testing and operation phases is obtained. Finally, the unknown parameters are estimated by the least-squares method based on normalized data set. Experiments show that the goodness-of-fit of the TO-SRGM is better than those of the G-O model and PZ-SRGM on a data set.