Exact Gap Computation for Code Coverage Metrics in ISO-C

Dirk Richter
(Martin-Luther-University of Halle-Wittenberg)
Christian Berg
(Martin-Luther-University of Halle-Wittenberg)

Test generation and test data selection are difficult tasks for model based testing. Tests for a program can be meld to a test suite. A lot of research is done to quantify the quality and improve a test suite. Code coverage metrics estimate the quality of a test suite. This quality is fine, if the code coverage value is high or 100%. Unfortunately it might be impossible to achieve 100% code coverage because of dead code for example. There is a gap between the feasible and theoretical maximal possible code coverage value. Our review of the research indicates, none of current research is concerned with exact gap computation. This paper presents a framework to compute such gaps exactly in an ISO-C compatible semantic and similar languages. We describe an efficient approximation of the gap in all the other cases. Thus, a tester can decide if more tests might be able or necessary to achieve better coverage.

In Alexander K. Petrenko and Holger Schlingloff: Proceedings 7th Workshop on Model-Based Testing (MBT 2012), Tallinn, Estonia, 25 March 2012, Electronic Proceedings in Theoretical Computer Science 80, pp. 43–57.
Published: 27th February 2012.

ArXived at: https://dx.doi.org/10.4204/EPTCS.80.4 bibtex PDF
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