Application of Neural Networks to Software Quality Modeling of A Very Large Telecommunications System  

Oleh:

Aud, S. J. ; Hudepohl, J. P. ; Khoshgoftaar, T. M. ; Allen, E.B.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 8 no. 4 (1997), page 902-909.
Topik: telecommunications; neural networks; software quality; telecommunication system

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Society relies on telecommunications to such an extent that telecommunications software must have high reliability. Enhanced measurement for early risk assessment of latent defects (EMERALD) is a joint project of Nortel and Bell Canada for improving the reliability of telecommunications software products. This paper reports a case study of neural - network modeling techniques developed for the EMERALD system. The resulting neural network is currently in the prototype testing phase at Nortel. Neural-network models can be used to identify fault-prone modules for extra attention early in development, and thus reduce the risk of operational problems with those modules. We modeled a subset of modules representing over seven million lines of code from a very large telecommunications software system. The set consisted of those modules reused with changes from the previous release. The dependent variable was membership in the class of fault - prone modules. The independent variables were principal components of nine measures of software design attributes. We compared the neural-network model with a non parametric discriminant model and found the neural -network model had better predictive accuracy.

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