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
Design science in information systems research
(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
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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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Should computer scientists experiment more? https://app.cochat.ai/papers/10.1109/2.675631
- The paper
- Tichy, W. F. (1998). Should computer scientists experiment more? Computer. https://doi.org/10.1109/2.675631
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.
