Data generation in model-based testing

Authors:
Padmanabhan Krishnan;Percy Pari-Salas
Affiliations:
Bond University, Gold Coast, QLD, Australia;Bond University, Gold Coast, QLD, Australia
Venue:
Proceedings of the 2010 ACM Symposium on Applied Computing
Year:
2010

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Abstract

In this paper we show how context free grammars extended with limited state information can be used to enhance model-based testing. Abstract models can be made more specific using the values generated by these grammars. The approach allows the association of data to the model without changing the model itself. We present two examples to illustrate the applicability of the framework. We also show how this approach is implemented in a real model-based testing tool.