Towards a scalable cloud platform for search-based probabilistic testing

• 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.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Software Engineering (hsv//eng)

Nyckelord

Cloud platforms

Deterministic technique

Input datas

Optimisations

Probabilistic testing

Search-based

Test sets

Publikations- och innehållstyp

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