Tool support for automatically constructing analysis models from the natural language specification of requirements (NLR) is critical to model driven development (MDD), as it can bring forward the use of precise formal languages from the coding to the specification phase in the MDD lifecycle. TRAM provides such a support through a novel approach. By using a set of conceptual patterns to facilitate the transformation of an NLR to its target software model, TRAM has shown its potential as an automated tool to support the earliest phase of MDD. This paper describes TRAM and evaluates the tool against three benchmark approaches.

Textual specification documents do not represent a suitable starting point for software development. This issue is due to the inherent problems of natural language such as ambiguity, impreciseness and incompleteness. In order to overcome these shortcomings, experts derive analysis models such as requirements models. However, these models are difficult and costly to create manually. Furthermore, the level of abstraction of the models is too low, thus hindering the automated transformation process. We propose a novel approach which uses high abstraction requirements models in the form of Object System Models (OSMs) as targets for the transformation of natural language specifications in conjunction with appropriate text mining and machine learning techniques. OSMs allow the interpretation of the textual specification based on a small set of facts and provide structural and behavioral information. This approach will allow both (1) the enhancement of minimal specifications, and in the case of comprehensive specifications (2) the determination of the most suitable structure of reusable requirements.