Name
Abstract | ||
|---|---|---|
A relevant objective of software reliability assessment is to get unbiased estimates with an acceptable trade-off between the number of tests required and the variance of the estimate. A low variance is desirable to increase the confidence in the estimate, but too many tests may be required by conventional reliability assessment testing techniques based solely on the operational profile. This article presents probabilistic sampling-based testing, a new technique using unequal probability sampling to exploit auxiliary information about the software under test so as to assess reliability unbiasedly and efficiently. The technique expedites the assessment process assuming the availability of some prior belief about input regions failure proneness. The evaluation by simulation and experimentally shows promising results in terms of estimate accuracy and efficiency. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/QRS.2018.00017 | 2018 IEEE International Conference on Software Quality, Reliability and Security (QRS) |
Keywords | Field | DocType |
Reliability assessment, SRGM, random testing, operational testing, reliability testing, debug testing | Computer science,Exploit,Software,Sampling (statistics),Probabilistic logic,Software quality,Reliability engineering | Conference |
ISBN | Citations | PageRank |
978-1-5386-7758-2 | 3 | 0.38 |
References | Authors | |
31 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto Pietrantuono | 1 | 357 | 30.48 |
| Stefano Russo | 2 | 728 | 78.07 |