Prediction of Software Reliability Using Connectionist Models
Prediction of Software Reliability Using Connectionist Models
复制标题
DOI：
10.1109/32.148475
复制
发表时间：
1992-07
期刊：
影响因子：
--
通讯作者：
N. Karunanithi;L. D. Whitley;Y. Malaiya
中科院分区：
文献类型：
--
作者：
N. Karunanithi;L. D. Whitley;Y. Malaiya
说明了联结主义模型对软件可靠性增长预测的实用性。使用各种网络模型，训练制度和数据表示方法的连接主义方法的适用性进行了探讨。使用来自几个不同软件项目的实际数据集，这种方法和五个著名的软件可靠性增长模型之间的实证比较。研究结果表明，联结主义模型可以很好地适应不同的数据集，并表现出更好的预测准确性。分析表明，连接主义的方法是能够开发不同的复杂性模型。>
The usefulness of connectionist models for software reliability growth prediction is illustrated. The applicability of the connectionist approach is explored using various network models, training regimes, and data representation methods. An empirical comparison is made between this approach and five well-known software reliability growth models using actual data sets from several different software projects. The results presented suggest that connectionist models may adapt well across different data sets and exhibit a better predictive accuracy. The analysis shows that the connectionist approach is capable of developing models of varying complexity. >