Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
158 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Towards an Approach to Pattern-based Domain-Specific Requirements Engineering (2404.17338v1)

Published 26 Apr 2024 in cs.SE

Abstract: Requirements specification patterns have received much attention as they promise to guide the structured specification of natural language requirements. By using them, the intention is to reduce quality problems related to requirements artifacts. Patterns may need to vary in their syntax (e.g. domain details/ parameter incorporation) and semantics according to the particularities of the application domain. However, pattern-based approaches, such as EARS, are designed domain-independently to facilitate their wide adoption across several domains. Little is yet known about how to adopt the principle idea of pattern-based requirements engineering to cover domain-specificity in requirements engineering and, ideally, integrate requirements engineering activities into quality assurance tasks. In this paper, we propose the Pattern-based Domain-specific Requirements Engineering Approach for the specification of functional and performance requirements in a holistic manner. This approach emerges from an academia-industry collaboration and is our first attempt to frame an approach which allows for analyzing domain knowledge and incorporating it into the requirements engineering process enabling automated checks for requirements quality assurance and computer-aided support for system verification. Our contribution is two-fold: First, we present a solution to pattern-based domain-specific requirements engineering and its exemplary integration into quality assurance techniques. Second, we showcase a proof of concept using a tool implementation for the domain of flight controllers for Unmanned Aerial Vehicles. Both shall allow us to outline next steps in our research agenda and foster discussions in this direction.

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com