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Software reliability growth with test
coverage
Malaiya, Y.K. Li, M.N.
Bieman,
J.M. Karcich, R.
Dept. of Comput. Sci., Colorado State Univ., Fort Collins,
CO;
This paper appears
in: Reliability, IEEE Transactions on
Publication Date: Dec 2002
On page(s): 420- 426
Volume: 51, Issue: 4
ISSN:
0018-9529
Abstract:
"Software test-coverage measures" quantify the
degree of thoroughness of testing. Tools are now available that
measure test-coverage in terms of blocks, branches,
computation-uses, predicate-uses, etc. that are covered. This paper
models the relations among testing time, coverage, and reliability.
An LE (logarithmic-exponential) model is presented that relates
testing effort to test coverage (block, branch, computation-use, or
predicate-use). The model is based on the hypothesis that the
enumerable elements (like branches or blocks) for any coverage
measure have various probabilities of being exercised; just like
defects have various probabilities of being encountered. This model
allows relating a test-coverage measure directly with
defect-coverage. The model is fitted to 4 data-sets for programs
with real defects. In the model, defect coverage can predict the
time to next failure. The LE model can eliminate variables like
test-application strategy from consideration. It is suitable for
high reliability applications where automatic (or manual) test
generation is used to cover enumerables which have not yet been
tested. The data-sets used suggest the potential of the proposed
model. The model is simple and easily explained, and thus can be
suitable for industrial use. The LE model is based on the time-based
logarithmic software-reliability growth model. It considers that: at
100% coverage for a given enumerable, all defects might not yet have
been found.
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