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Cited by 723

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Why interaction is more powerful than algorithms

Open access
Wegner, Peter·1997·Communications of the ACM

Abstract

The article goes into the reason behind interaction being more powerful than algorithms. Interaction is a more powerful paradigm than rule-based algorithms for computer problem-solving, overturning the prevailing view that all computing is expressible as algorithms. The paradigm shift from algorithms to interaction captures the technology shift from mainframes to workstations and networks, from number-crunching to embedded systems and graphical user interfaces, and from procedure-oriented to object-based and distributed programming. The radical notion that interactive systems are more powerful problem-solving engines than algorithms is the basis for a new paradigm for computing technology built around the unifying concept of interaction. Whereas interaction histories express the external unfolding of events in time, instruction-execution histories express an ordering of inner events of an algorithm without any relation to the actual passage of time. Algorithmic time is intentionally measured by number of instructions executed, rather than by the actual time taken by execution.

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Crossref · 10.1145/253769.253801

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Metadata

Authors
Wegner, P.
Venue
Communications of the ACM
Published
1997-05
Volume
40
Issue
5
Pages
80-91
ISSN
  • 0001-0782 (ISSN-L)
  • 1557-7317
OpenAlex
W2141955344
Cited by
723
References
1
FWCI
43.75
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Why interaction is more powerful than algorithms. https://app.cochat.ai/papers/10.1145/253769.253801
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Wegner, P. (1997). Why interaction is more powerful than algorithms. Communications of the ACM. https://doi.org/10.1145/253769.253801

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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.