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Qualitative Simulation of Models of Software Evolution

Ramil, Juan F. and Smith, Neil (2002). Qualitative Simulation of Models of Software Evolution. Software Process: Improvement and Practice, 7(3-4) pp. 95–112.

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Lehman's laws and the quantitative models based on them seek to encapsulate empirical generalizations about E-type program evolution. Such modelling is hampered by insufficient knowledge about the mechanisms at work and their parameters. Qualitative reasoning is a body of work that handles a lack of precise knowledge by reasoning at a more abstract level than with quantitative models. This paper describes the introduction of qualitative reasoning to the study of software evolution. It reports on the derivation of qualitative versions of two existing quantitative models of the software evolution process, leading to identification of previously unrecognized behaviours. A third qualitative model is also discussed. The paper also shows how qualitative trend abstraction enables a high level of abstraction analysis of empirical data and that, at this level, the empirical patterns observed in several different software systems display similarities. Finally, we compare the qualitative simulation outputs of the three systems to the abstracted empirical trends.

Item Type: Journal Item
ISSN: 1077-4866
Keywords: empirical generalizations; laws of software evolution; qualitative simulation; software metrics; software process; simulation models
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 4704
Depositing User: Neil Smith
Date Deposited: 11 Jul 2006
Last Modified: 01 May 2019 13:23
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