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Qualitative simulation model for software engineering process

Authors: He Zhang 0001; Ming Huo; Barbara A. Kitchenham; D. Ross Jeffery;

Qualitative simulation model for software engineering process

Abstract

Software process simulation models hold out the promise of improving project planning and control. However, quantitative models require a very detailed understanding of the software process. In particular, process knowledge needs to be represented quantitatively which requires extensive, reliable software project data. When such data is lacking, quantitative models must impose severe constraints, restricting the value of the models. In contrast qualitative models are able to cope with imprecise knowledge by reasoning at a more abstract level. This paper illustrates the value and flexibility of qualitative models by developing a model of the software staffing process and comparing it with other quantitative staffing models. We show that the qualitative model provides more insights into the staffing process than the quantitative models because it requires fewer constraints and can thus simulate more behaviors. In particular, the qualitative model produces three possible outcomes: adding staff can increases project duration (i.e. Brooks' Law), adding staff may not affect duration, or adding staff may decrease duration. The qualitative model allows us to determine the conditions under which the different outcomes can occur.

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    influence
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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!
16
Average
Top 10%
Top 10%
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