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Article . 1992 . Peer-reviewed
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Fitness Conditions for fixed Point Iteration

Authors: Flemming Nielson; Hanne Riis Nielson;

Fitness Conditions for fixed Point Iteration

Abstract

This paper provides a link between the formulation of static program analyses using the framework of abstract interpretation (popular for functional languages) and using the more classical framework of data flow analysis (popular for imperative languages). In particular we show how the classical notions of fastness, rapidity and k-boundedness carry over to the abstract interpretation framework and how this may be used to bound the number of times a functional should be unfolded in order to yield the fixed point. This is supplemented with a number of results on how to calculate the bounds for iterative forms (as for tail recursion), for linear forms (as for one nested recursive call), and for primitive recursive forms. In some cases this improves the ''worst case'' results of H.R. Nielson and F. Nielson: Bounded Fixed Point Iteration, but more importantly it gives much better ''average case'' results.

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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!
2
Average
Average
Average
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