Towards a Software Reference Architecture for Natural Language Processing Tools in Requirements Engineering

TL;DR

This paper proposes a software reference architecture to improve the interoperability, reuse, and sustainability of NLP tools in requirements engineering, addressing current fragmentation and maintenance issues.

Contribution

It introduces a research roadmap and initial stakeholder-driven requirements for developing a modular, interoperable ecosystem of NLP4RE tools.

Findings

Elicited 36 key system requirements for NLP4RE tools

Identified the need for a dedicated software reference architecture

Outlined a roadmap for future development of NLP4RE ecosystem

Abstract

Natural Language Processing (NLP) tools support requirements engineering (RE) tasks like requirements elicitation, classification, and validation. However, they are often developed from scratch despite functional overlaps, and abandoned after publication. This lack of interoperability and maintenance incurs unnecessary development effort, impedes tool comparison and benchmarking, complicates documentation, and diminishes the long-term sustainability of NLP4RE tools. To address these issues, we postulate a vision to transition from monolithic NLP4RE tools to an ecosystem of reusable, interoperable modules. We outline a research roadmap towards a software reference architecture (SRA) to realize this vision, elaborated following a standard methodological framework for SRA development. As an initial step, we conducted a stakeholder-driven focus group session to elicit generic system requirements for NLP4RE tools. This activity resulted in 36 key system requirements, further motivating the need for a dedicated SRA. Overall, the proposed vision, roadmap, and initial contribution pave the way towards improved development, reuse, and long-term maintenance of NLP4RE tools.