Abstract. This article presents the generation and test case execution under the framework Focal. In the programming language Focal, all properties of the program are written within the source code. These properties are considered, here, as the program specification. We are interested in testing the code against these properties. Testing a property is split in two stages. First, the property is cut out in several elementary properties. An elementary property is a tuple composed of some pre-conditions and a conclusion. Lastly, each elementary property is tested separately. The pre-conditions are used to generate and select the test cases randomly. The conclusion allows us to compute the verdict. All the testing process is done automatically.

In order to check requirement specifications written in natural language, we have chosen to model domain knowledge through an ontology and to formally represent user requirements by its population. Our approach of ontology population focuses on instance property identification from texts. We do so using extraction rules automatically acquired from a training corpus and a bootstrapping terminology. These rules aim at identifying instance property mentions represented by triples of terms, using lexical, syntactic and semantic levels of analysis. They are generated from recurrent syntactic paths between terms denoting instances of concepts and properties. We show how centring on instance property identification allows us to precisely identify concept instances explicitly or implicitly mentioned in texts.

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