The DOI matches its Crossref record.
Practical fast searching in strings
Abstract
The problem of searching through text to find a specified substring is considered in a practical setting. It is discovered that a method developed by Boyer and Moore can outperform even special‐purpose search instructions that may be built into the computer hardware. For very short substrings however, these special purpose instructions are fastest—provided that they are used in an optimal way.
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Citations
Cited by
Navarro, G., & Raffinot, M. (2002) · Cambridge University Press eBooks · doi:10.1017/cbo9781316135228 · Cited by 291
On-line string matching algorithms: survey and experimental results
Michailidis, P. D., & Margaritis, K. G. (2001) · International Journal of Computer Mathematics · doi:10.1080/00207160108805036 · Cited by 53
Efficient inverted index with n-gram sampling for string matching in Arabic documents
Nagoudi, E. M. B., Khorsi, A., & Cherroun, H. (2016) · 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA) · doi:10.1109/aiccsa.2016.7945743 · Cited by 1
Metadata
- Authors
- Horspool, R. N.
- Venue
- Software: Practice and Experience
- Publisher
- Wiley
- Published
- 1980-06
- Volume
- 10
- Issue
- 6
- Pages
- 501-506
- ISSN
- 0038-0644 (ISSN-L)
- 1097-024X
- OpenAlex
- W1986106281
- Cited by
- 594
- References
- 0
- FWCI
- 2.34
- Type
- journal article
- Language
- en
- Open access
- closed
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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: Practical fast searching in strings. https://app.cochat.ai/papers/10.1002/spe.4380100608
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- Horspool, R. N. (1980). Practical fast searching in strings. Software: Practice and Experience. https://doi.org/10.1002/spe.4380100608
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.
