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A method for overlapping and erasure of lists
Open accessAbstract
An important property of the Newell Shaw-Simon scheme for computer storage of lists is that data having multiple occurrences need not be stored at more than one place in the computer. That is, lists may be “overlapped.” Unfortunately, overlapping poses a problem for subsequent erasure. Given a list that is no longer needed, it is desired to erase just those parts that do not overlap other lists. In LISP, McCarthy employs an elegant but inefficient solution to the problem. The present paper describes a general method which enables efficient erasure. The method employs interspersed reference counts to describe the extent of the overlapping.
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Citations
Cited by
Collaboration Processes: Inside the Black Box
Thomson, A. M., & Perry, J. L. (2006) · Public Administration Review · doi:10.1111/j.1540-6210.2006.00663.x · Cited by 1,386
List processing in real time on a serial computer
Baker, H. G. (1978) · Communications of the ACM · doi:10.1145/359460.359470 · Cited by 592
Generation Scavenging: A non-disruptive high performance storage reclamation algorithm
Ungar, D. (1984) · ACM SIGSOFT Software Engineering Notes · doi:10.1145/390010.808261 · Cited by 484
Perceus: garbage free reference counting with reuse
Reinking, A., Xie, N., de Moura, L., & Leijen, D. (2021) · Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation · doi:10.1145/3453483.3454032 · Cited by 32
Metadata
- Authors
- Collins, G. E.
- Venue
- Communications of the ACM
- Published
- 1960-12
- Volume
- 3
- Issue
- 12
- Pages
- 655-657
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W1965601529
- Cited by
- 310
- References
- 0
- FWCI
- 3.67
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Collins, G. E. (1960). A method for overlapping and erasure of lists. Communications of the ACM. https://doi.org/10.1145/367487.367501
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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.