Performance-driven software development: an incremental refinement approach for high-quality requirement engineering

By increasing the importance of the performance in industrial and business software systems, efficient approaches to model-based performance engineering are becoming an inherent part of the development life cycle. Performance engineering at abstract levels of the software development process has an important effect on concluding the success of the software by obtaining the knowledge of optimal alternative designs. This paper introduces the performance-driven software development approach and a prediction technique that regards performance quality attributes at the abstract levels of the software development in an incremental refinement manner. The approach provides Z-based specification formalism at the meta-model level in which its instance models are automatically transformed into the formal performance analytical model, called refinable state machine (RSM). This paper analyses the throughput of a RSM by performing an approximation algorithm on two experimental case studies to determine weights of subjective performance characteristics. The approach can use the inherent performance parameters according to product usage and derive an incremental probabilistic policy determination method under design decisions in the performance plan hierarchy. The results exhibit significant support of abstract level performance profiling in terms of the throughput values.