Abstract A software model can be analysed for nonfunctional requirements by extending it with suitable annotations and transforming it into analysis models for the corresponding non-functional properties. For quantitative performance evaluation, suitable annotations are standardized in the "UML Profile for Modeling and Analysis of Real-Time Embedded systems" (MARTE) and its predecessor, the "UML Profile for Schedulability, Performance and Time". A range of different performance model types (such as queueing networks, Petri nets, stochastic process algebra) may be used for analysis. In this work, an intermediate "Core Scenario Model" (CSM) is used in the transformation from the source software model to the target performance model. CSM focuses on how the system behaviour uses the system resources. The semantic gap between the software model and the performance model must be bridged by (1) ibility is required for specifying sets of alternative cases, for choosing where this bridging information is supplied, and for overriding values. It is also essential to be able to trace the source of values used in a particular performance estimate. The performance model in turn can be used to verify responsiveness and scalability of a software system, to discover architectural limitations at an early stage of development, and to develop efficient performance tests. This paper describes how the semantic gap between software models in UML+MARTE and performance models (based on queueing or Petri nets) can be bridged using transformations based on CSMs, and how the transformation challenges are addressed.
Other approaches for performance analysis try to derive Petri net performance models from UML diagrams with standardised annotations in the "UML Profile for Modelling and Analysis of Real-Time Embedded systems" (MARTE) REF .
Transformation challenges: from software models to performance models
Software & Systems Modeling
Software & Systems Modeling
Computer Science