A Deductive Approach for Fault Localization in ATL Model Transformations

Massimo Tisi 1, 2 Zheng Cheng 2
2 AtlanModels - Modeling Technologies for Software Production, Operation, and Evolution
Inria Rennes – Bretagne Atlantique , LS2N - Laboratoire des Sciences du Numérique de Nantes
Abstract : In model-driven engineering, correct model transformation is essential for reliably producing the artifacts that drive software development. While the correctness of a model transformation can be specified and checked via contracts, debugging unverified contracts imposes a heavy cognitive load on transformation developers. To improve this situation, we present an automatic fault localization approach, based on natural deduction, for the ATL model transformation language. We start by designing sound natural deduction rules for the ATL language. Then, we propose an automated proof strategy that applies the designed deduction rules on the postconditions of the model transformation to generate sub-goals: successfully proving the sub-goals implies the satisfaction of the postconditions. When a sub-goal is not verified, we present the user with sliced ATL model transformation and predicates deduced from the postcondition as debugging clues. We provide an automated tool that implements this process. We evaluate its practical applicability using mutation analysis, and identify its limitations.
Type de document :
Communication dans un congrès
FASE 2017 - 20th International Conference on Fundamental Approaches to Software Engineering, Apr 2017, Uppsala, Sweden
Liste complète des métadonnées

Littérature citée [30 références]  Voir  Masquer  Télécharger

https://hal.archives-ouvertes.fr/hal-01435977
Contributeur : Zheng Cheng <>
Soumis le : lundi 16 janvier 2017 - 09:38:30
Dernière modification le : jeudi 26 octobre 2017 - 13:38:24

Fichier

FASE.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01435977, version 1

Collections

Citation

Massimo Tisi, Zheng Cheng. A Deductive Approach for Fault Localization in ATL Model Transformations. FASE 2017 - 20th International Conference on Fundamental Approaches to Software Engineering, Apr 2017, Uppsala, Sweden. 〈hal-01435977〉

Partager

Métriques

Consultations de
la notice

253

Téléchargements du document

141