From UML descriptions of High-Level software architectures to LQN performance models

Abstract

Performance characteristics as response time and throughput play an important role in defining the quality of software products. The software developers should be able to assess and understand the performance effects of various architectural decisions starting at an early stage, when changes are easy and less expensive, and continuing throughout the software life cycle. This can be achieved by constructing and analyzing quantitative performance models that capture the interactions between the main system components and point to the system’s performance trouble spots. The paper proposes a formal approach to building Layered Queueing Network (LQN) performance models from Unified Modeling Language (UML) descriptions of the high-level architecture of a system, and more exactly from the architectural patterns used in the system. The performance modeling formalism, LQN, is an extension of the well-known Queueing Network modelling technique. The transformation from a UML architectural description of a given system to its LQN model is based on PROGRES, a well-known visual language and environment for programming with graph rewriting systems.