
A Multi-Level Approach to KPI Definition, Configuration and Computation for Executable Domain-Specific Languages In this project, we assist domain experts and end users in evaluating the performance of their systems during the design phase, before a real implementation. Therefore, we propose a multi-level MultiLevel4KPI approach that enables performance assessment across heterogeneous xDSLs and their systems without modifying the original languages. The approach involves three roles operating at specific levels: a Language Engineer, a Domain Expert, and an End User. At the top level, the language engineer designs the xDSL itself, while the domain expert and end user collaborate on performance evaluation at their own abstraction level. The approach is mainly based on the Generic Performance Evaluation Language (GPEL), a generic performance language that relies on a Trace Domain Query Language (TraceDQL) to help extract data from the execution traces of simulated models for Key Performance Indicator (KPI) computation.
Reconfigurable Manufacturing Systems, Domain-Specific Language, Execution Trace, Key Performance Indicators, Model Execution, Trace Domain Query Language
Reconfigurable Manufacturing Systems, Domain-Specific Language, Execution Trace, Key Performance Indicators, Model Execution, Trace Domain Query Language
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
