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Quality Attribute Refinement and Allocation

Dr. Neil Ernst discusses industry practices such as slicing and ratcheting used to develop business capabilities and suggests approaches to enable large-scale iteration.

Software Engineering Institute




We know from existing SEI work on attribute-driven design, Quality Attribute Workshops, and the Architecture Tradeoff Analysis Method that a focus on quality attributes prevents costly rework. Such a long-term perspective, however, can be hard to maintain in a high-tempo, agile delivery model, which is why the SEI continues to recommend an architecture-centric engineering approach, regardless of the software methodology chosen. As part of our work in value-driven incremental delivery, we conducted exploratory interviews with teams in these high-tempo environments to characterize how they managed architectural quality attribute requirements (QARs). These requirements—such as performance, security, and availability—have a profound impact on system architecture and design, yet are often hard to divide, or slice, into the iteration-sized user stories common to iterative and incremental development. This difficulty typically exists because some attributes, such as performance, touch multiple parts of the system. In this podcast, Neil Ernst discusses research on slicing (refining) performance in two production software systems and ratcheting (periodic increase of a specific response measure) of scenario components to allocate QAR work.

About the Speaker

Headshot of Neil Ernst

Neil Ernst

Neil Ernst is an SEI alumni employee.

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