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Applying non-constant volatility analysis methods to software timeliness.

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dc.contributor.author Brennan, Shane
dc.contributor.author Cahill, Vinny
dc.contributor.author Clarke, Siobhán
dc.date.accessioned 2012-03-14T16:15:12Z
dc.date.available 2012-03-14T16:15:12Z
dc.date.issued 2009
dc.identifier.uri http://hdl.handle.net/10344/2088
dc.description peer-reviewed en_US
dc.description.abstract Timing analysis is the application of one or more well-established predictive methods to derive the likely timing behaviour of a specific software task executing on a particular hardware platform. Current approaches towards timing analysis are predicated on the presumption that the software under test is always fixed, i.e., it remains unchanged once deployed to the target hardware. A dynamically adaptable system modifies its behaviour in unanticipated ways, and at unpredictable intervals, to exploit the prevailing operational environment. However, when the software is capable of runtime adaptation, statically derived timing estimates are incapable of accurately capturing the changes in the software timeliness caused by functional adaptations. Traditional timing analysis methods cannot be applied to a dynamically adaptive system, due to the inconstant nature of the software, the unpredictable scheduling of functional adaptations, and the need to produce timing estimates at runtime. This paper describes a work in progress with the aim of statistically forecasting software timeliness using non-constant volatility methods. We outline how timing bounds may be derived for an adaptable software system, with changeable underlying functionality, and show how timing predictions can be modified, using novel statistical models, to mirror runtime functional changes to the software. en_US
dc.language.iso eng en_US
dc.relation.ispartofseries Proceedings of the 21st Euromicro Conference on Real-Time Systems.;2009
dc.subject software en_US
dc.subject timing analysis en_US
dc.title Applying non-constant volatility analysis methods to software timeliness. en_US
dc.type Conference item en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.type.restriction none en
dc.contributor.sponsor SFI
dc.relation.projectid 03/CE2/I303_1

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