Software Model Refactoring Driven by Performance Antipattern Detection

Abstract

The satisfaction of ever more stringent performance requirements is one of the main reasons for software evolution. However, determining the primary causes of performance degradation is generally challenging, as they may depend on the joint combination of multiple factors (e.g., workload, software deployment, hardware utilization). With the increasing complexity of software systems, classical bottleneck analysis seems to show limitations in capturing complex performance problems. Hence, in the last decade, the detection of performance antipatterns has gained momentum as an effective way to identify performance degradation causes. In this tool paper we introduce PADRE (Performance Antipattern Detection and REfactoring), a tool for: (i) detecting performance antipattern in UML models, and (ii) refactoring models with the aim of removing the detected antipatterns. PADRE has been implemented within Epsilon, which is an open-source platform for model-driven engineering, and it grounds on a methodology that allows performance antipattern detection and refactoring within the same implementation context.