ExANT: GSSE completes project with prototype for formalization of natural language requirements and derivation of tests

Requirements for technical systems are still predominant today written in natural language text. The transformation of the text into a formal notation for implementation in code and derivation of test cases is still be done manually. This transformation is automated by using artificial intelligence (AI).

In the ExANT project, GSSE addressed an automated and AI-supported process for the transformation of natural language requirements into a formal and executable notation, to check the conformity to specified rules, the correctness and completeness of the requirements, and to provide a feedback for the revision of the requirements.

Using the spaCy Natural Language Processing (NLP) tool the text is broken down into syntactic elements and classified semantically. By a rule-based approach clauses are derived from which test objectives are identified. The test objectives are transformed into executable code by using the oracle approach. Verification of the requirements shall be performed by using the oracles.

Furthermore, statistics, lists of objects and correlations between objects as well as enumerations are derived, and coreferences are resolved.

The implementation was done in Python. It is possible to generate code for the oracles in other languages.

The project was funded by the Federal Ministry for Economic Affairs and Climate Action as part of the National Program for Space and Innovation and was technically and administratively managed by the German Space Agency at DLR.