Performance is a critical non-functional parameter for real-time systems and performance analysis is an important task making it more challenging for complex real-time systems. Mostly performance analysis is performed after the system development but an early stage analysis and validation of performance using system models can improve the system quality. In this paper, we present an early stage automated performance evaluation methodology to analyse system performance using the UML sequence diagram model annotated with modeling and analysis of real-time and embedded systems (MARTE) profile. MARTE offers a performance domain sub-profile that is used for representing real-time system properties essential for performance evaluation. In this paper, a transformation technique and transformation rules are proposed to map the UML sequence diagram model into a Generalized Stochastic Timed Petri net model. All the transformation rules are implemented using a metamodel based approach and Atlas Transformation Language (ATL). A case study from the manufacturing domain a Kanban system is used for validating the proposed technique.

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Real-time systems are complex and composed of time-bounded events that must satisfy the real-time constraints for their proper functioning. To cope with the complexity of real-time systems, model-driven approaches such as model-driven architecture (MDA) can be followed, which uses the conceptual models for system representation. This paper presents an MDA-based automated approach for an early stage performance evaluation and verification of a real-time system using the Unified Modeling Language (UML)/Modeling and Analysis of Real-Time and Embedded systems (MARTE) sequence diagram. A metamodel-based model-to-model transformation technique is used for mapping the UML/MARTE sequence diagram into the generalized Petri Net Markup Language (PNML) representation of the timed Petri net model using Atlas Transformation Language (ATL). The derived PNML representation has the advantage to support the interoperability between different Petri nettools when compared over the existing methods that produce tool-specific representation. The proposed approach enables the system designers to create and evaluate alternate system designs and predict their behavior, contributing to improving the system quality. The contribution of the proposed technique for identifying the optimal system design is analyzed using a real-time embedded sensor application. The proposed transformation approach is also validated using a real-time system from the manufacturing domain.