DocumentCode :
3067043
Title :
A case study of the recursive least squares estimation approach to adaptive testing for software components
Author :
Hu, Hai ; Wong, W. Eric ; Jiang, Chang-Hai ; Cai, Kai-Yuan
Author_Institution :
Dept. of Comput. Sci., Texas Univ., Richardson, TX, USA
fYear :
2005
fDate :
19-20 Sept. 2005
Firstpage :
135
Lastpage :
141
Abstract :
The strategy used for testing a software system should not be fixed, because as time goes on we may have a better understanding of the software under test. A solution to this problem is to introduce control theory into software testing. We can use adaptive testing where the testing strategy is adjusted on-line by using the data collected during testing. Since the use of software components in software development is increasing, it is now more important than ever to adopt a good strategy for testing software components. In this paper, we use an adaptive testing strategy for testing software components. This strategy (AT_RLSEc with c indicating components) applies a recursive least squares estimation (RLSE) method to estimate parameters such as failure detection rate. It is different from the genetic algorithm-based adaptive testing (AT_GA) where a genetic algorithm is used for parameter estimation. Experimental data from our case study suggest that the fault detection effectiveness of AT_RLSEc is better than that of AT_GA and random testing.
Keywords :
adaptive control; failure analysis; genetic algorithms; least squares approximations; object-oriented programming; program testing; recursive estimation; AT_RLSEc strategy; adaptive testing; control theory; failure detection rate; fault detection; genetic algorithm; parameter estimation; random testing; recursive least squares estimation; software component; software development; software testing; Control theory; Fault detection; Genetic algorithms; Least squares approximation; Parameter estimation; Programming; Recursive estimation; Software systems; Software testing; System testing; adaptive testing; controlled Markov chain; software cybernetics; software testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Quality Software, 2005. (QSIC 2005). Fifth International Conference on
ISSN :
1550-6002
Print_ISBN :
0-7695-2472-9
Type :
conf
DOI :
10.1109/QSIC.2005.1
Filename :
1579129
Link To Document :
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