Paper Info
Title
Normalized Adaptive Random Test for Integration Tests
Abstract
The Adaptive Random Testing (ART) was devised to improve the performance of pure random tests, which is one of black-box testing strategies. The ART-based algorithms were developed mainly for unit or single module tests. When a given unit-under-test (UUT) is integrated with an already proven front-end software module which takes inputs and supplies the outputs to the UUT, the performance of ART-based algorithm applied to the integrated software is severely degraded depending on the behavior of front-end software. In this paper, a normalized ART-based algorithm is proposed for the integration and regression tests where an UUT is integrated with a front-end software module. The front-end software with three different functions, Log, Exponential, and Normal function, is experimented by the simulation to show the performance of the proposed method. Depending on the skewness driven by the function of front-end, the experimental results show that the proposed method outperforms significantly the ART without normalization in terms of F-measure.
Year
DOI
Venue
2010
10.1109/COMPSACW.2010.65
COMPSAC Workshops
Keywords
Field
DocType
program testing,regression analysis,random test,integration tests,front end software,art based algorithm,adaptive random testing,unit under test,regression test,blackbox testing strategy,normalized adaptive random test,normal function,test case selection,front-end software,art-based algorithm,exponential function,integration test,front-end software module,f-measure,integration testing,normalized art-based algorithm,log function,software engineering,single module test,different function,integrated software,regression testing,black box testing,f measure,front end,random testing
Random testing,Normalization (statistics),Skewness,Integration testing,Computer science,Algorithm,Regression testing,Real-time computing,Dynamic testing,Software,Integrated software,Reliability engineering
Conference
ISBN
Citations 
PageRank 
978-0-7695-4105-1
3
0.40
References 
Authors
0
4
Name
Order
Citations
PageRank
Seung-Hun Shin1123.85
Seung-Kyu Park2458.87
Kyunghee Choi38314.14
Ki-Hyun Jung416714.59