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http://bura.brunel.ac.uk/handle/2438/11881
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DC Field | Value | Language |
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dc.contributor.author | Hierons, RM | - |
dc.contributor.author | Turker, U | - |
dc.date.accessioned | 2016-01-21T14:45:43Z | - |
dc.date.available | 2016-01-21T14:45:43Z | - |
dc.date.issued | 2009 | - |
dc.identifier.citation | The Computer Journal, (2009) | en_US |
dc.identifier.issn | 1460-2067 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/11881 | - |
dc.description.abstract | This paper concerns the problem of testing from a finite state machine (FSM) M modelling a system that interacts with its environment at multiple physically distributed interfaces, called ports. We assume that the distributed test architecture is used: there is a local tester at each port, the tester at port p only observes events at p, and the testers do not interact during testing. This paper formalises the notion of an adaptive test strategy and what it means for an adaptive test strategy to be controllable. We provide algorithms to check whether a global strategy is controllable and to generate a controllable adaptive distinguishing sequence (ADS). We prove that controllable ADS existence is PSPACE-hard and that the problem of deciding whether M has a controllable ADS with length l is NP-hard. In practice, there is likely to be a polynomial upper bound on the length of ADS in which we are interested and for this case the decision problem is NP-complete. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Oxford University Press (OUP): Policy A - Oxford Open Option A | en_US |
dc.subject | Finite state machine | en_US |
dc.subject | Distributed test architecture | en_US |
dc.subject | Distinguishing sequences | en_US |
dc.title | Distinguishing Sequences for Distributed Testing: Adaptive Distinguishing Sequences | en_US |
dc.type | Article | en_US |
dc.relation.isPartOf | The Computer Journal | - |
pubs.publication-status | Accepted | - |
pubs.publication-status | Accepted | - |
Appears in Collections: | Dept of Computer Science Research Papers |
Files in This Item:
File | Description | Size | Format | |
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Fulltext.pdf | 1.04 MB | Adobe PDF | View/Open |
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