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End-to-end Fine-grained Traceability Analysis in Model Transformations and Transformation Chains Open Access


Other title
software engineering
model-driven engineering
code generation
computer science
software maintenance
Type of item
Degree grantor
University of Alberta
Author or creator
Guana Garces, Victor
Supervisor and department
Eleni Stroulia (Computing Science)
Examining committee member and department
James Miller (Electrical & Computer Engineering)
Kenny Wong (Computing Science)
Eleni Stroulia (Computing Science)
Jeff Gray (Computing Science - University of Alabama)
Abram Hindle (Computing Science)
Department of Computing Science

Date accepted
Graduation date
2017-11:Fall 2017
Doctor of Philosophy
Degree level
Over the last few decades, model-driven code generation has been the flagship paradigm used to promote adoption of model-driven engineering among the general software-engineering community. Model-driven code generators integrate model-to-model and model-to-text transformations to build applications that systematically differ from each other. Typically, generators use multi-step transformation chains to translate high-level application specifications, captured using domain-specific languages, into executable artifacts such as code and deployment scripts. A key challenge in the construction of development environments for model transformations involves the analysis and visualization of traceability information. Access to fine-grained traceability links enables developers to assess evolutionary scenarios in transformation ecosystems, to effectively debug complex binding expressions, and to accurately determine the metamodel coverage of transformation chains. Unfortunately, current traceability-analysis techniques do not consider implicit bindings when collecting traceability information from complex transformation expressions. Implicit bindings manipulate, constrain, or navigate the structure of a metamodel in order to realize the final intent of a transformation expression. Furthermore, they do not conceive model-to-model and model-to-text transformations as equal constituent elements of a unified model-driven engineering toolbox. This effectively limits their usability in the context of non-trivial model-driven code generators. To the best of our knowledge, the effectiveness of current traceability analysis, and the development environments built on top of them, has not been validated in empirical studies with real developers. In this work, we address these shortcomings. We propose an end-to-end fine-grained traceability-analysis technique for individual model-to-model and model-to-text transformations, as well as model-transformation chains combining the two. Our analysis technique is based on a traceability framework that considers traceability links as symbolic dependencies between metamodels, transformation expressions, and generated artifacts. Furthermore, we introduce ChainTracker, a traceability-analysis environment. We evaluated the completeness of our traceability-analysis technique using 25 model-to-model and 18 model-to-text transformations from the ATLZoo and the Acceleo Example Repository. Our analysis technique achieved an overall fine-grained traceability coverage of 91\% and 85\%, respectively. Furthermore, we evaluated the usability of ChainTracker in an empirical study in which 25 developers completed traceability-driven tasks in two model-driven code generators of different complexity. We found statistically significant evidence that ChainTracker improves the accuracy and efficiency of developers by between 22\% and 900\%.
This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for the purpose of private, scholarly or scientific research. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
Citation for previous publication
Guana, V., Eleni, S. End-to-end Model-transformation Comprehension Through Fine-grained Traceability Information. International Journal on Software and Systems Modeling (SoSYM), 2017.Guana, V., Stroulia, E. Reflecting on Model-based Code Generators Using Traceability Information. 18th International Conference on Model Driven Engineering Languages and Systems (MODELS) - Tool Demo. Sep. 27-28, 2015. Ottawa, Canada.Guana, V., Gaboriau, K. Stroulia, E. ChainTracker: Towards a Comprehensive Tool for Building Code-generation Environments. 30th IEEE International Conference on Software Maintenance and Evolution (ICSM) - Tool Demo. Sep 27 - October 3, 2014. Victoria, Canada.Guana, V. Supporting Maintenance Tasks on Transformational Code Generation Environments. Doctoral Symposium, 35th International Conference on Software Engineering (ICSE). May 18-26, 2013. San Francisco. USA.Guana, V., Eleni, S. Traceability Analysis in Model-to-Model and Model-to-Text Transformations and Transformation Chains. International Journal on Software and Systems Modeling (SoSYM), 2017 (submitted)Guana, V., Stroulia, E.: ChainTracker, a Model-transformation Trace Analysis Tool for Code-generation Environments. 7th International Conference on Model Transformation (ICMT). July 21-25. 2014. York, UK.Guana, V., Stroulia, E., Nguyen, V. Building a Game Engine: A Tale of Modern Model-Driven Engineering. 4th International Workshop on Games and Software Engineering (GAS15). May 18, 2015. Florence, Italy.Guana, V., Stroulia, E. PhyDSL: A Code-generation Environment for 2D Physics-based Games. IEEE Games, Entertainment, and Media Conference (IEEE GEM). October 22-24, 2014. Toronto. Canada.

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