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Nigel Stanger imageBSc, MSc, PhD(Otago), MIITP
Lecturer

Ōwheo Building, 2.05
Tel +64 3 479 8179
Email nigel.stanger@otago.ac.nz

Background and interests

Dr Nigel Stanger teaches at 200, 300, and 400 level, covering topics such as database design, management and administration, relational and object / relational database systems, distributed data management, and data warehousing. His research interests include digital preservation, digital repositories, data management of all kinds, data model translation, data integration, physical database design and database performance, and information visualisation.

Dr Stanger is also the webmaster and South Island representative for:
the New Zealand Oracle Users' Group (NZOUG)

Dr Stanger is also the recipient of a Teaching Award.

Papers

  • COMP101 Foundations of Information Systems
  • INFO 201 Developing Information Systems 1
  • INFO 202 Developing Information Systems 2
  • INFO 303 Enterprise Information Systems Infrastructure
  • INFO 408 Management of Large-Scale Data

Supervision

Currently co-supervising

  • Pankaj Sharma
  • Elijah Zoldouarrati

Publications

Chambers, T., Dean, F., Klavs, J., Stanger, N., Kim, A., Hales, S., Douwes, J., Baker, M. G., & Deng, J. (2026). A national-scale historical assessment of nitrate in public drinking water supplies in New Zealand: Data integration and machine learning imputation approaches. Water Environment Research, 98(2), e70296. doi: 10.1002/wer.70296 Journal - Research Article

Zolduoarrati, E., Licorish, S. A., & Stanger, N. (2025). Comprehensive predictive analytics for collaborators' answers, code quality, and dropout: Stack overflow case study. Empirical Software Engineering, 30, 147. doi: 10.1007/s10664-025-10692-4 Journal - Research Article

Zolduoarrati, E., Licorish, S. A., & Stanger, N. (2025). Stack overflow’s hidden nuances: How does zip code define user contribution? Journal of Systems & Software, 223, 112374. doi: 10.1016/j.jss.2025.112374 Journal - Research Article

Zolduoarrati, E., Licorish, S. A., & Stanger, N. (2024). Harmonising contributions: Exploring diversity in software engineering through CQA mining on Stack Overflow. ACM Transactions on Software Engineering & Methodology, 33(7), 179. doi: 10.1145/3672453 Journal - Research Article

Grattan, N., Alencar da Costa, D., & Stanger, N. (2024). The need for more informative defect prediction: A systematic literature review. Information & Software Technology, 171, 107456. doi: 10.1016/j.infsof.2024.107456 Journal - Research Article

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