Model-driven Performance Measurement and Assessment with Relational Traces

Boskovic, Marko (2009) Model-driven Performance Measurement and Assessment with Relational Traces (Doctoral thesis/PhD), University of Oldenburg, Oldenburg, 172 pp


Download (1877Kb) | Preview


Model Driven Engineering is an emerging approach in software development which argues using models as primary software artifacts. The models can vary from prescriptive ones specied in Domain Specic Modeling Languages (DSMLs), for the domain specic software development (e.g. Graphical User Interfaces DSML), to descriptive models for analysis, such as queuing networks and Petri-nets. The main benet of such approach is that it reduces the time and eort spent in implementation by transforming the domain specic prescriptive models to the code. Furthermore, performance characteristics of the implementation can be predicted during the design phase with usage of transformation of domain specic constructs to formal mathematical models. For software performance, as an important software Quality of Service attribute, several approaches for prediction exist in MDE. However, MDE still lacks a systematic approach for performance measurement and metrics assessment. This thesis presents MoDePeMART, an approach for Model Driven Performance Measurement and Assessment with Relational Traces. The approach suggests declarative specication of performance metrics in a domainspeci c language and the usage of relational databases for storage and metric computation. The approach is evaluated with the implementation of a UML Prole for UML Class and State diagrams and transformations from the prole to a commercial relational database management system.

Document Type: Thesis (Doctoral thesis/PhD)
Thesis Advisors: UNSPECIFIED
Keywords: Model-driven Performance Measurement and Assessment
Research affiliation: Kiel University > Software Engineering
Date Deposited: 11 Jun 2012 08:24
Last Modified: 31 Aug 2013 20:24

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...