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Embracing change with extreme programming
Abstract
Traditional software engineering means have been characterized by a rather predictable process in the past. Users tell once and for all exactly what they want. Programmers design the system that will deliver those features. They code it; test it, and all is well. But all was not always well. The users did not tell once and for all exactly what they wanted. They changed their minds, and the users were not the only problem. Programmers could misjudge their progress. The academic software engineering community took the high cost of changing software as a challenge, creating technologies like relational databases, modular programming, and information hiding. This is where extreme programming comes in. Rather than planning, analyzing, and designing for the far-flung future, XP exploits the reduction in the cost of changing software to do all of these activities a little at a time, throughout software development. The paper discusses the major practices of XP.
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Cited by
A Framework and Guidelines for Context-Specific Theorizing in Information Systems Research
Hong, W., Chan, F. K. Y., Thong, J. Y. L., Chasalow, L. C., & Dhillon, G. (2014) · Information Systems Research · doi:10.1287/isre.2013.0501 · Cited by 609
Chaste: An Open Source C++ Library for Computational Physiology and Biology
Mirams, G. R., Arthurs, C. J., Bernabeu, M. O., Bordas, R., Cooper, J., Corrias, A., Davit, Y., Dunn, S.-J., Fletcher, A. G., Harvey, D. G., et al. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002970 · Cited by 423
Usage, costs, and benefits of continuous integration in open-source projects
Hilton, M., Tunnell, T., Huang, K., Marinov, D., & Dig, D. (2016) · Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering · doi:10.1145/2970276.2970358 · Cited by 342
User acceptance of agile information systems: a model and empirical test
Hong, W., Thong, J. Y. L., Chasalow, L. C., & Dhillon, G. (2011) · Journal of Management Information Systems · doi:10.2753/mis0742-1222280108 · Cited by 212
Measuring and predicting software productivity: A systematic map and review
Petersen, K. (2011) · Information and Software Technology · doi:10.1016/j.infsof.2010.12.001 · Cited by 128
Metadata
- Authors
- Beck, K.
- Venue
- Computer
- Published
- 1999
- Volume
- 32
- Issue
- 10
- Pages
- 70-77
- ISSN
- 0018-9162 (ISSN-L)
- OpenAlex
- W2113848838
- Cited by
- 979
- References
- 0
- FWCI
- 43.73
- Type
- journal article
- Language
- en
- Open access
- closed
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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.