Extracting Quality Attributes from User Stories for Early Architecture Decision Making

Abstract

Software quality attributes (e.g., security, performance) influence software architecture design decisions, e.g., when choosing technologies, patterns or tactics. As software developers are moving from big upfront design to an evolutionary or emerging design, the architecture of a system evolves as more functionality is added. In agile software development, functional user requirements are often expressed as user stories. Quality attributes might be implicitly referenced in user stories. To support a more systematic analysis and reasoning about quality attributes in agile development projects, this paper explores how to automatically identify quality attributes from user stories. This could help better understand relevant quality attributes (and potential architectural key drivers) before analysing product backlogs and domains in detail and provides the “bigger picture” of potential architectural drivers for early architecture decision making. The goal of this paper is to present our vision and preliminary work towards understanding whether user stories do include information about quality attributes at all, and if so, how we can identify such information in an automated manner.