Swinburne
Browse
- No file added yet -

Towards the software engineering of neural networks: a maturity model

Download (52.3 kB)
conference contribution
posted on 2024-07-12, 12:28 authored by Anthony Senyard, Philip Dart, Leon SterlingLeon Sterling
Neural networks are being used increasingly in a wide range of real world applications. However, existing studies have reported major problems in neural network software development. This paper analyses these problems, and describes how existing software engineering practice can address some of them. Other problems are identified as requiring new approaches tailored to neural network development. A unified framework is presented, in the form of an extension to the Capability Maturity Model, aimed at instituting good software engineering practice for neural network development. The framework should be of interest to neural network software developers, and suggests research directions towards the software engineering of neural networks.

History

Available versions

PDF (Published version)

ISBN

9780769506319

Journal title

12th Australian Software Engineering Conference (ASWEC 2000), Canberra, Australia, 28-29 August 2000 / Douglas D. Grant (ed.)

Conference name

12th Australian Software Engineering Conference ASWEC 2000, Canberra, Australia, 28-29 August 2000 / Douglas D. Grant ed.

Issue

1

Pagination

6 pp

Publisher

IEEE

Copyright statement

Copyright © 2000 IEEE. The published version is reproduced in accordance with the copyright policy of the publisher. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Language

eng

Usage metrics

    Publications

    Categories

    No categories selected

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC