Automating Performance Antipattern Detection and Software Refactoring in UML Models
| Autor: | Davide Arcelli, Daniele Di Pompeo, Vittorio Cortellessa |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Model-Driven Development
Software Performance business.industry Computer science 020207 software engineering Context (language use) 02 engineering and technology computer.software_genre Bottleneck Software Code refactoring Unified Modeling Language Software deployment 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Software system Software engineering business computer Software evolution computer.programming_language |
| Zdroj: | SANER 2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER) |
| DOI: | 10.1109/saner.2019.8667967 |
| Popis: | The satisfaction of ever more stringent performance requirements is one of the main reasons for software evolution. However, it is complex to determine the primary causes of performance degradation, because 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 shows 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. We introduce PADRE (Performance Antipattern Detection and REfactoring), that is 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, an open-source platform for model-driven engineering. It is based on a methodology that allows performance antipattern detection and refactoring within the same implementation context. |
| Databáze: | OpenAIRE |
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