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Towards a scalable cloud platform for search-based probabilistic testing
Blekinge Institute of Technology, School of Computing.
Blekinge Institute of Technology, School of Computing.
2013 (English)Conference paper (Refereed) Published
Abstract [en]

Probabilistic testing techniques that sample input data at random from a probability distribution can be more effective at detecting faults than deterministic techniques. However, if overly large (and therefore expensive) test sets are to be avoided, the probability distribution from which the input data is sampled must be optimised to the particular software-under-test. Such an optimisation process is often resource-intensive. In this paper, we present a prototypical cloud platform-and architecture-that permits the optimisation of such probability distributions in a scalable, distributed and robust manner, and thereby enables cost-effective probabilistic testing.

Place, publisher, year, edition, pages
Eindhoven: IEEE , 2013.
Keyword [en]
Cloud platforms, Deterministic technique, Input datas, Optimisations, Probabilistic testing, Search-based, Test sets
National Category
Software Engineering
URN: urn:nbn:se:bth-6728DOI: 10.1109/ICSM.2013.77Local ID: diva2:834261
IEEE International Conference on Software Maintenance (ICSM)
Available from: 2014-04-15 Created: 2014-04-15 Last updated: 2015-06-30Bibliographically approved

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Poulding, SimonFeldt, Robert
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