Random Grammar-based Testing for Covering All Non-Terminals
This work addresses the challenge of efficient grammar-based testing for software developers, presenting an incremental improvement over existing random or coverage-based methods.
The paper tackles the problem of generating complex data inputs for software testing by combining random generation with coverage criteria, specifically biasing random generation to optimize the probability of covering all non-terminals in a grammar.
In the context of software testing, generating complex data inputs is frequently performed using a grammar-based specification. For combinatorial reasons, an exhaustive generation of the data -- of a given size -- is practically impossible, and most approaches are either based on random techniques or on coverage criteria. In this paper, we show how to combine these two techniques by biasing the random generation in order to optimise the probability of satisfying a coverage criterion.