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)

TL;DR
This paper introduces a framework for precisely calculating the gap between achievable and theoretical maximum code coverage in ISO-C, aiding testers in improving test suites by understanding coverage limitations.
Contribution
It presents the first exact gap computation method for code coverage metrics in ISO-C and offers an efficient approximation for similar languages.
Findings
Exact gap computation framework for ISO-C
Efficient approximation method for other cases
Enables better test suite optimization
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
