A Classification Framework of Uncertainty in Architecture-Based Self- Adaptive Systems with Multiple Quality Requirements
نویسندگان
چکیده
Context: The underlying uncertainty in self-adaptive systems aggravates the complexity of selecting best adaptation action alternative, and handling requirements trade-offs. To efficiently tackle uncertainty, it is necessary to have a comprehensive overview of different types of uncertainty and their specifications. Objective: In this paper we aim at a) reviewing the state-of-the-art of architecture-based approaches tackling uncertainty in self-adaptive systems with multiple quality requirements, b) proposing a classification framework for this domain, and c) classifying the current approaches according to this framework. Method: We conducted a systematic literature review by performing an automatic search on twenty seven selected venues and books in the domain of self-adaptive systems. Results: We propose a classification framework for uncertainty and its sources in the domain of architecture-based self-adaptive systems with multiple quality requirements. We map 51 identified primary studies into the framework and present the classified results. Conclusions: Our results help researchers to understand the current state of research regarding uncertainty in architecture-based self-adaptive systems with multiple concerns, and identity areas for improvement in the future.
منابع مشابه
A Protocol for a Classification Framework of Uncertainty in Architecture-based Self-Adaptive Systems with Multiple Quality Requirements
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