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Chaos of Software Requirements

Authors: Junwei Ge; Yiqiu Fang; Shayne Flint;

Chaos of Software Requirements

Abstract

Evolving model of software requirements is very important to the success of software engineering, but we need theoretical principles to lead us to do it. According to the nonlinear dynamic requirements decomposition equations developed by us based on the nonlinear dynamic system, we discuss the chaotic phenomena of software requirements through simulations mainly in the paper. It is impossible for us to get all sub-requirements through requirements decomposition when the decomposition is in chaos. The occurrence of chaos is determined by requirements decomposition rate parameter (RDRP). The change of initial values of requirements may cause a large change of decomposed results, but will not affect the occurrence of chaos. When RDRP is too large, a small change may cause the decomposition into an unstable state from a stable state. The decomposition may also be in chaos even if it is nearly completed when RDRP is unsuitable. Therefore, it is better for us to let the decomposition outside chaos to get full sub-requirements.

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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!
1
Average
Average
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