为了更好地保障试运行软件的运行效果，引入加权马尔可夫链构建试运行软件缺陷预测模型。利用加权马尔可夫链的非线性运算量，对试运行软件进行测评及优化，建立基于加权马尔可夫链的软件缺陷预测平台，在平台的空间范围内计算影响软件运行精度的相关参数，以此降低软件运行过程中的数据维度，提高试运行软件缺陷预测的精度和收敛速度。实验结果表明，在实际应用过程中，所设计预测模型能够精准预测试运行软件的缺陷，具有较高的实用价值，充分满足研究要求。

In order to better guarantee the running effect of the trial run software, the weighted Markov chain is introduced to construct the software defect prediction model. By using the nonlinear computation of weighted Markov chain, the software defect prediction platform based on weighted Markov chain is established, and the relevant parameters affecting the software operation accuracy are calculated within the space scope of the platform, so as to reduce the data dimension in the process of software operation, and improve the accuracy and convergence speed of software defect prediction. The experimental results show that, in the actual application process, the prediction model designed can accurately predict the defects of the test run software, has high practical value, and fully meets the research requirements.