Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICSM.2013.77 | Software Maintenance |
Keywords | Field | DocType |
cloud computing,program testing,statistical distributions,cost-effective probabilistic testing,probability distribution,scalable cloud platform,search-based probabilistic testing,software-under-test | Data mining,Orthogonal array testing,Computer science,Software performance testing,Software reliability testing,Probability distribution,Probabilistic logic,Cloud testing,Scalability,Cloud computing | Conference |
ISSN | Citations | PageRank |
1063-6773 | 1 | 0.34 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Louis M. Rose | 1 | 522 | 34.34 |
| Simon M. Poulding | 2 | 136 | 10.72 |
| Robert Feldt | 3 | 335 | 29.03 |
| Richard F. Paige | 4 | 23 | 2.84 |