An enhanced neural network technique for software risk analysis
Abstract
An enhanced technique for risk categorization is presented. This technique, PCA-ANN, provides an improved capability to discriminate high-risk software. The approach draws on the combined strengths of pattern recognition, multivariate statistics and neural networks. Principal component analysis is utilized to provide a means of normalizing and orthogonalizing the input data, thus eliminating the ill effects of multicollinearity. A neural network is used for risk determination/classification. A significant feature of this approach is a procedure, herein termed cross-normalization. This procedure provides the technique with capability to discriminate data sets that include disproportionately large numbers of high-risk software modules.
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High collinearity among input variables can result in model non-convergence, inconsistent results and degraded model performance.
“This can result in model non-convergence, inconsistent results and degraded model performance (Walczak & Cerpa 1999, Neumann 2002).”
From Comparison between environmental characteristics of larval bluefin tuna Thunnus thynnus habitat in the Gulf of Mexico and western Mediterranean Sea (2013) · cites this paper as Neumann 2002
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Muhling, B., Reglero, P., Ciannelli, L., Alvarez-Berastegui, D., Alemany, F., Lamkin, J., & Roffer, M. (2013) · Marine Ecology Progress Series · doi:10.3354/meps10397 · Cited by 58 · see citing works
- Authors
- Neumann, D. E.
- Affiliations
- General Dynamics (United States) (US)
- Corresponding author
- Neumann, D.E.
- Venue
- IEEE Transactions on Software Engineering
- Published
- 2002-09
- Volume
- 28
- Issue
- 9
- Pages
- 904-912
- ISSN
- 0098-5589 (ISSN-L)
- OpenAlex
- W2114077012
- Cited by
- 127
- References
- 0
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 2 · 2022: 7 · 2021: 1 · 2020: 5 · 2019: 5 · 2018: 6 · 2017: 7 · 2016: 7 · 2015: 8 · 2014: 8 · 2013: 8 · 2012: 5
- FWCI
- 3.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Software Engineering (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Software › Software Reliability and Analysis Research
- Keywords
- software risk analysis, risk classification, principal component analysis, artificial neural networks, multicollinearity
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