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Effect of code coverage on software
reliability measurement
Chen,
M.-H. Lyu, M.R. Wong, W.E.
Dept. of Comput. Sci., State Univ. of
New York, Albany, NY;
This
paper appears in: Reliability, IEEE Transactions
on
Publication
Date: Jun 2001
On page(s):
165-170
Volume: 50,
Issue:
2
ISSN:
0018-9529
References Cited:
21
CODEN: IERQAD
Abstract:
Existing software reliability-growth models
often over-estimate the reliability of a given program. Empirical
studies suggest that the over-estimations exist because the models
do not account for the nature of the testing. Every testing
technique has a limit to its ability to reveal faults in a given
system. Thus, as testing continues in its region of saturation, no
more faults are discovered and inaccurate reliability-growth
phenomena are predicted from the models. This paper presents a
technique intended to solve this problem, using both time and code
coverage measures for the prediction of software failures in
operation. Coverage information collected during testing is used
only to consider the effective portion of the test data. Execution
time between test cases, which neither increases code coverage nor
causes a failure, is reduced by a parameterized factor. Experiments
were conducted to evaluate this technique, on a program created in a
simulated environment with simulated faults, and on two industrial
systems that contained tenths of ordinary faults. Two well-known
reliability models, Goel-Okumoto and Musa-Okumoto, were applied to
both the raw data and to the data adjusted using this technique.
Results show that over-estimation of reliability is properly
corrected in the cases studied. This new approach has potential, not
only to achieve more accurate applications of software reliability
models, but to reveal effective ways of conducting software testing
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