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Part of book or chapter of book
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https://doi.org/10.1007/119153...
Part of book or chapter of book . 2006 . Peer-reviewed
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DBLP
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Algorithmic Thinking: The Key for Understanding Computer Science

Authors: Gerald Futschek;

Algorithmic Thinking: The Key for Understanding Computer Science

Abstract

We show that algorithmic thinking is a key ability in informatics that can be developed independently from learning programming. For this purpose we use problems that are not easy to solve but have an easily understandable problem definition. A proper visualization of these problems can help to understand the basic concepts connected with algorithms: correctness, termination, efficiency, determinism, parallelism, etc. The presented examples were used by the author in a pre-university course, they may also be used in secondary schools to help understanding some concepts of computer science.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
120
Top 1%
Top 1%
Average
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