Detecting performance bad smells for Henshin model transformations

Matthias Tichy, Christian Krause, Grischa Liebel

Research output: Contribution to journalConference articlepeer-review

14 Citations (Scopus)


In model-driven software engineering, model transformations are used for the specification of model changes. Similar to programs also model transformations can exhibit bad smells which indicate possible weaknesses. In this paper, we address bad smells which can negatively affect the performance of the application of model transformations, particularly, model transformations defined in Henshin. Based on a description of the Henshin interpreter and its performance enhancing strategies, we describe a set of bad smells and corresponding detectors. We evaluate the detectors by applying them to the example rule set of Henshin.

Original languageEnglish
JournalCEUR Workshop Proceedings
Publication statusPublished - 2013
Event2nd Workshop on the Analysis of Model Transformations, AMT 2013 - Miami, United States
Duration: 29 Sept 2013 → …

Bibliographical note

Publisher Copyright:
Copyright © 2013 for the individual papers by the papers' authors.

Other keywords

  • Bad smell
  • Henshin
  • Model transformation
  • Performance
  • Subgraph matching


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