Transformation of sequence diagram to timed Petri net using Atlas Transformation Language metamodel approach

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 net tools 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. This paper presents a metamodel‐based automated transformation technique for mapping the UML/MARTE sequence diagram into the generalized PNML representation of the timed Petri net model using the ATL Transformation Language. The proposed approach supports interoperability between different Petri net tools using the PNML format. The paper also demonstrates how the system models play a key role in the early stage system verification and analyzing the performance of alternate system design to select the optimal option.