Controllable combinatorial coverage in grammar-based testing. Given a grammar (or other sorts of meta-data), one can trivially derive combinatorially exhaustive test-data sets up to a specified depth. Without further efforts, such test-data sets would be huge at the least and explosive most of the time. Fortunately, scenarios of grammar-based testing tend to admit non-explosive approximations of naive combinatorial coverage. In this paper, we describe the notion of controllable combinatorial coverage and a corresponding algorithm for test-data generation. The approach is based on a suite of control mechanisms to be used for the characterization of test-data sets as well-defined and understandable approximations of full combinatorial coverage. The approach has been implemented in the C#-based test-data generator Geno, which has been successfully used in projects that required differential testing, stress testing and conformance testing of grammar-driven functionality.
References in zbMATH (referenced in 5 articles , 1 standard article )
Showing results 1 to 5 of 5.
- Héam, Pierre-Cyrille; Masson, Catherine: A random testing approach using pushdown automata (2011)
- Lämmel, Ralf; Zaytsev, Vadim: An introduction to grammar convergence (2009)
- Demakov, A. V.; Zelenov, S. V.; Zelenova, S. A.: Using abstract models for the generation of test data with a complex structure (2008)
- Zybin, R. S.; Kuliamin, V. V.; Ponomarenko, A. V.; Rubanov, V. V.; Chernov, E. S.: Automation of broad sanity test generation (2008)
- Lämmel, Ralf; Schulte, Wolfram: Controllable combinatorial coverage in grammar-based testing (2006)