Exact Gap Computation for Code Coverage Metrics in ISO-C
This work addresses a specific gap in model-based testing for ISO-C and similar languages, offering incremental improvements in test suite quality assessment.
The paper tackles the problem of quantifying the gap between feasible and theoretical maximum code coverage in ISO-C programs, presenting a framework for exact gap computation and an efficient approximation for other cases.
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.