The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Can genetic programming improve software effort estimation? A comparative evaluation
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Citations
Cites
An Introduction to Genetic Algorithms
Mitchell, M. (1996) · doi:10.7551/mitpress/3927.001.0001 · Cited by 11,340
Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches
Aamodt, A., & Plaza, E. (1994) · AI Communications · doi:10.3233/aic-1994-7104 · Cited by 5,624
Heuristic principles for the design of artificial neural networks
Walczak, S., & Cerpa, N. (1999) · Information and Software Technology · doi:10.1016/s0950-5849(98)00116-5 · Cited by 195
Cited by
The Current State and Future of Search Based Software Engineering
Harman, M. (2007) · Future of Software Engineering (FOSE '07) · doi:10.1109/fose.2007.29 · Cited by 631
Systematic literature review of machine learning based software development effort estimation models
Wen, J., Li, S., Lin, Z., Hu, Y., & Huang, C. (2012) · Information and Software Technology · doi:10.1016/j.infsof.2011.09.002 · Cited by 526
A Survey of Evolutionary Algorithms for Decision-Tree Induction
Barros, R. C., Basgalupp, M. P., de Carvalho, A. C. P. L. F., & Freitas, A. A. (2012) · IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/tsmcc.2011.2157494 · Cited by 346
Data mining techniques for software effort estimation: a comparative study
Dejaeger, K., Verbeke, W., Martens, D., & Baesens, B. (2012) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2011.55 · Cited by 224
Metadata
- Authors
- Burgess, C. J., & Lefley, M.
- Venue
- Information and Software Technology
- Publisher
- Elsevier BV
- Published
- 2001-12
- Volume
- 43
- Issue
- 14
- Pages
- 863-873
- ISSN
- 0950-5849 (ISSN-L)
- OpenAlex
- W2043584165
- Cited by
- 300
- References
- 3
- FWCI
- 21.69
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Can genetic programming improve software effort estimation? A comparative evaluation. https://app.cochat.ai/papers/10.1016/s0950-5849(01)00192-6
- The paper
- Burgess, C. J., & Lefley, M. (2001). Can genetic programming improve software effort estimation? A comparative evaluation. Information and Software Technology. https://doi.org/10.1016/s0950-5849(01)00192-6
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
