Deriving Architectural Responsibilities from Textual Requirements

RODRIGUEZ, GUILLERMO; DIAZ PACE, ANDRÉS; BERDUN, LUIS S.; MISRA, SANJAY

Ota

Conferencia; International Conference on Informatics and Intelligent Applications; 2022

Natural language is widely used to write software requirements. Generally, software designers start with textual requirements and realize them into a first architectural design. A common problem in this transition is the conceptual gap between the requirements space and the software architecture space. To assist designers in the task, we propose an AI-based approach for deriving high-level architecture descriptions expressed as Use Case Maps (UCMs) from textual requirements. Our approach consists of three steps: (i) identification of responsibilities from functional requirements, (ii) extraction of causal relationships between the responsibilities, and (iii) allocation of the responsibilities to architectural components. Thus, designers can obtain a first view of a software solution that covers both structural and behavioral aspects. This view is useful for assessing architecture alternatives or for further design refinements. The approach relies on NLP and Data Mining techniques. An experimental evaluation with four case studies revealed that our approach detected on average 75% of the responsibilities in term of F-measure.