The DOI matches its Crossref record.
Should computer scientists experiment more?
Abstract
Computer scientists and practitioners defend their lack of experimentation with a wide range of arguments. Some arguments suggest that experimentation is inappropriate, too difficult, useless, and even harmful. This article discusses several such arguments to illustrate the importance of experimentation for computer science. It considers how the software industry is beginning to value experiments, because results may give a company a three- to five-year lead over the competition.
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Citations
Cited by
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Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004) · MIS Quarterly · doi:10.2307/25148625 · Cited by 10,707
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(2004) · Journal of the Association for Information Systems · doi:10.5555/2017212.2017217 · Cited by 8,254
Guidelines for conducting and reporting case study research in software engineering
Runeson, P., & Höst, M. (2009) · Empirical Software Engineering · doi:10.1007/s10664-008-9102-8 · Cited by 3,862
(2015) · doi:10.1007/s10664-013-9279-3 · Cited by 273
The ABC of Software Engineering Research
Stol, K.-J., & Fitzgerald, B. (2018) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3241743 · Cited by 245
Issues in bioinformatics benchmarking: the case study of multiple sequence alignment
Aniba, M. R., Poch, O., & Thompson, J. D. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq625 · Cited by 72
Benchmarking as Empirical Standard in Software Engineering Research
Hasselbring, W. (2021) · Evaluation and Assessment in Software Engineering · doi:10.1145/3463274.3463361 · Cited by 40
Metadata
- Authors
- Tichy, W. F.
- Venue
- Computer
- Published
- 1998-05
- Volume
- 31
- Issue
- 5
- Pages
- 32-40
- ISSN
- 0018-9162 (ISSN-L)
- OpenAlex
- W2113294746
- Cited by
- 487
- References
- 0
- FWCI
- 37.91
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
