A Domain-Specific Framework for Priority-Based Modeling and Optimization of Non-Functional Requirements Beyond Binary Constraints

Non-Functional Requirements (NFRs) such as performance, security, reliability, and usability significantly influence the overall quality of software systems. However, traditional NFR engineering approaches commonly treat these requirements as binary constraints, i.e., either fully satisfied or not, which limits systematic trade-off reasoning even in conventional single-system software architectures. This limitation becomes critical in complex, dynamic domains such as IoT and cyber-physical systems, where multiple interdependent NFRs must coexist without degrading system performance. To address this challenge, this paper proposes a domain-specific framework for modeling and optimizing priority-based NFRs beyond binary constraints. The framework integrates standard well-recognized quality models like ISO/IEC 25010 and FURPS+, to identify domain-specific NFRs, which are then modeled as soft goals with graded degrees of satisfaction. Priority weights, utility-based reasoning, and multi-objective optimization are integrated to manage conflicts and trade-offs among competing NFRs while preserving system stability. Unlike traditional approaches that enforce a rigidly defined subset of NFRs, the proposed framework enables the combination of multiple NFRs proportionally according to their priority and contextual relevance. The framework is applicable to diverse software-intensive systems including IoT, cloud platforms, healthcare systems, and cyber-physical environments. This work contributes a systematic, scalable, and adaptive approach to proactive NFR management suitable for modern software systems. The concrete research problem addressed is the failure of binary NFR handling in dynamic adaptation settings, leading to over-constrained designs or degraded quality. The framework guarantees improved global utility (15-25% in simulations) and adaptation success (>90%) while maintaining performance thresholds, with low runtime overhead (~O(n2) for n NFRs).