Paper Info
Title
On Adaptive Sampling-Based Testing for Software Reliability Assessment
Abstract
Assessing reliability of software programs during validation is a challenging task for engineers. The assessment is not only required to be unbiased, but it needs to provide tight variance (hence, tight confidence interval) with as few test cases as possible. Statistical sampling is a theoretically sound approach for reliability testing, but it is often impractical in its current form, because of too many test cases required to achieve desired confidence levels, especially when the software has few residual faults inside. We claim that the potential of statistical sampling methods is largely underestimated. This paper presents an adaptive sampling-based testing (AST) strategy for reliability assessment. A two-stage conceptual framework is defined, where adaptiveness is included to uncover residual faults earlier, while various sampling-based techniques are proposed to improve the efficiency (in terms of variance-test cases tradeoff) by better exploiting the information available to tester. An empirical study is conducted to assess the AST performance and compare the proposed sampling techniques to each other on real programs.
Year
DOI
Venue
2016
10.1109/ISSRE.2016.50
2016 IEEE 27th International Symposium on Software Reliability Engineering (ISSRE)
Keywords
Field
DocType
Reliability assessment,sampling,random testing,statistical testing,operational testing,reliability testing,adaptive testing,software testing
Data mining,Computer science,Adaptive sampling,Software performance testing,Software,Software reliability testing,Sampling (statistics),Test case,Software quality,Reliability engineering,Reliability theory
Conference
ISSN
ISBN
Citations 
1071-9458
978-1-4673-9003-3
5
PageRank 
References 
Authors
0.41
32
2
Name
Order
Citations
PageRank
Roberto Pietrantuono135730.48
Stefano Russo272878.07