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Using Simulation for Assessing the Real Impact of Test Coverage on Defect Coverage

 
: Briand, L.C.; Pfahl, D.

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Fulltext urn:nbn:de:0011-px-586032 (211 KByte PDF)
MD5 Fingerprint: 6dcd25513a3f20dfb177ef7df58edc41
Created on: 09.08.2000


Kaiserslautern, 1999, VII, 20 pp. : Ill., Lit.
IESE-Report, 0018.99/E
Reportnr.: IESE-Report 018.99/E
English
Report, Electronic Publication
Fraunhofer IESE ()
defect coverage; simulation; software test; test coverage; test intensity

Abstract
The use of test coverage measures (e.g., block coverage) to control the software test process has become an increasingly common practice. This is justified by the assumption that higher test coverage helps achieve higher defect coverage and therefore improves software quality. In practice, data often shows that defect coverage and test coverage grow over time, as additional testing is performed. However, it is unclear whether this phenomenon of concurrent growth can be attributed to a causal dependency, or if it is coincidental, simply due to the cumulative nature of both measures. Answering such a question is important as it determines whether a given test coverage measure should be monitored for quality control and used to drive testing. Although this is no general answer to the problem above, we propose a procedure to investigate whether any test coverage criterion has a genuine additional impact on defect coverage when compared to the impact of just running additional test cases. T his procedure is applicable in typical testing conditions where the software is tested once, according to a given strategy, and where coverage measures are collected as well as defect data. We then test the procedure on published data and compare our results with the original findings. The study outcomes do not support the assumption of a causal dependency between test coverage and defect coverage, a result for which several plausible explanations are provided.

: http://publica.fraunhofer.de/documents/PX-58603.html