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Creator |
19fae8a5f7d2e4e1a37e5eefa7a11543 |
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Creator |
4343a6703bb74a32c59d641ada50d747 |
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Creator |
bf36d691dbc1b8c5a4fd560f3dc38c18 |
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Date |
2005-09 |
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Is Part Of |
repository |
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Is Part Of |
p10774866 |
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abstract |
Simulation modelling of growth trends and other empirical data from software systems
can reveal the main drivers of software evolution and help improve understanding and
management of the software evolution phenomenon. This article reports on the application
of qualitative abstraction techniques to data from 25 open source software (OSS) systems.
After justifying the use of qualitative simulation techniques for the software process
domain, the article presents an analysis of the support from OSS-derived data to previously
developed qualitative simulation models, which were inspired by observations from
the domain of proprietary systems. The analysis involved comparison of model output
and qualitatively abstracted growth trends. The analysis also involved the comparison
of the transitions in trends of functional size and complexity to those predicted
by the models in a sub-set of 21 systems for which complexity data was available.
The results indicate that models are able to replicate some of the features in the
data. This, in turn, suggests that the study of the relationship between size and
complexity and its interaction via feedback loops has a role in explaining the long-term
evolutionary behaviour of OSS systems. This is not surprising since it is well known
that the evolution of all type of real-world software systems, proprietary and OSS,
is driven by feedback from their stakeholders. |
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authorList |
authors |
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issue |
3 |
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status |
peerReviewed |
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volume |
10 |
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type |
AcademicArticle |
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type |
Article |
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label |
Smith, Neil ; Capiluppi, Andrea and Ramil, Juan F. (2005). A Study of Open Source
Evolution Data using Qualitative Simulation. Software Process: Improvement and Practice,
10(3) pp. 287–300. |
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label |
Smith, Neil ; Capiluppi, Andrea and Ramil, Juan F. (2005). A Study of Open Source
Evolution Data using Qualitative Simulation. Software Process: Improvement and Practice,
10(3) pp. 287–300. |
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Title |
A Study of Open Source Evolution Data using Qualitative Simulation |
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in dataset |
oro |