Analysis of error processes in computer software
Analysis of error processes in computer software
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DOI：
10.1145/800027.808456
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发表时间：
1975-06
期刊：
影响因子：
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通讯作者：
N. Schneidewind
中科院分区：
文献类型：
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作者：
N. Schneidewind
一个非齐次泊松过程被用来模拟在指挥和控制软件的功能测试过程中检测到的错误的发生。检测过程中的参数估计，通过使用最大似然法和加权最小二乘法的组合。一旦获得参数估计值，就可以对检测到的错误的累积数量进行预测。由检测误差函数导出累积校正误差、检测到但未校正的误差以及检测或校正指定数目的误差所需的时间的预测方程。不同的预测提供决策辅助管理软件测试活动。海军战术数据系统软件误差数据被用来评估预测方法的几种变化，并测试预测方程的精度。由于在实际检测误差过程中发生的变化，发现最近的误差观测比早期观测更能代表未来的误差发生。根据有限的测试模型，可以接受的精度时，使用首选的预测方法。
A non-homogeneous Poisson process is used to model the occurrence of errors detected during functional testing of command and control software. The parameters of the detection process are estimated by using a combination of maximum likelihood and weighted least squares methods. Once parameter estimates are obtained, forecasts can be made of cumulative number of detected errors. Forecasting equations of cumulative corrected errors, errors detected but not corrected, and the time required to detect or correct a specified number of errors, are derived from the detected error function. The various forecasts provide decision aids for managing software testing activities. Naval Tactical Data System software error data are used to evaluate several variations of the forecasting methodology and to test the accuracy of the forecasting equations. Because of changes which take place in the actual detected error process, it was found that recent error observations are more representative of future error occurrences than are early observations. Based on a limited test of the model, acceptable accuracy was obtained when using the preferred forecasting method.