Efficient Software Verification: Statistical Testing Using Automated Search

Statistical testing has been shown to be more efficient at detecting faults in software than other methods of dynamic testing such as random and structural testing. Test data are generated by sampling from a probability distribution chosen so that each element of the software's structure is exe...

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Bibliographic Details
Published in:IEEE transactions on software engineering Vol. 36; no. 6; pp. 763 - 777
Main Authors: Poulding, Simon, Clark, John A
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2010
IEEE Computer Society
Subjects:
Algorithms
Application software
Automated
Automatic testing
Automation
Computer programs
Digital Object Identifier
Dynamics
Efficiency
Fault detection
Faults
Flow graphs
Hypotheses
Optimization
Probability distribution
Sampling
Sampling methods
Searching
Software
Software algorithms
Software engineering
Software testing
Software/program verification
Statistical analysis
Studies
test coverage of code
Test methods
Test sets
testing strategies
ISSN:0098-5589, 1939-3520
Online Access:Get full text
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Summary:Statistical testing has been shown to be more efficient at detecting faults in software than other methods of dynamic testing such as random and structural testing. Test data are generated by sampling from a probability distribution chosen so that each element of the software's structure is exercised with a high probability. However, deriving a suitable distribution is difficult for all but the simplest of programs. This paper demonstrates that automated search is a practical method of finding near-optimal probability distributions for real-world programs, and that test sets generated from these distributions continue to show superior efficiency in detecting faults in the software.
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ISSN:0098-5589
1939-3520
DOI:10.1109/TSE.2010.24