Barriers to systematic model transformation testing

Abstract

Introduction Model Driven Engineering (MDE) techniques support extensive use of models in order to manage the increasing complexity of software systems. Appropriate abstractions of software system elements can ease reasoning and understanding and thus limit the risk of errors in large systems. Automatic model transformations play a critical role in MDE since they automate complex, tedious, error-prone, and recurrent software development tasks. Airbus uses automatic code synthesis from SCADE models to generate the code for embedded controllers in the Airbus A380. Commercial tools for model transformations exist. Objecteering and Together from Borland are tools that can automatically add design patterns in a UML class model. Esterel Technologies have a tool for automatic code synthesis for safety critical systems. Other examples of transformations are refinement of a design model by adding details pertaining to a particular target platform, refactoring a model by changing its structure to enhance design quality, or reverse engineering code to obtain an abstract model. These software development tasks are critical and thus the model transformations that automate them must be validated. A fault in a transformation can introduce a fault in the transformed model, which if undetected and not removed, can propagate to other models in successive development steps. As a fault propagates across transformations, it becomes more difficult to detect and isolate. Since model transformations are meant to be reused, faults present in them may result in many faulty models. Model transformations constitute a class of programs with unique characteristics that make testing them challenging. The complexity of input and output data, lack of model management tools, and the heterogeneity of transformation languages pose special problems to testers of transformations. In this paper we identify current model transformation characteristics that contribute to the difficulty of systematically testing transformations. We present promising solutions and propose possible ways to overcome these barriers.

Tractable Model Transformation Testing

“…One of the challenges of model transformation testing is the heterogeneity of model transformation languages and techniques [4]. This problem is aggravated by the possibility of having to test model transformations which are defined as a composition of several model transformations chained together.…”

“…Although more powerful than our approach from a theoretical perspective, their computational complexity generally makes them inappropriate for testing large model transformations. In addition, the drawback of a white-box approach is that it is tightly coupled to the transformation language and thus it would need to be adapted or completely redefined for another transformation language [4].…”

“…Testing model transformations is not an easy task and present numerous challenges [1,2,3,4]. In the literature there are two main approaches to model transformation testing (see also Section 5).…”

ATLTest: A White-Box Test Generation Approach for ATL Transformations

“…Among the possible strategies to improve the quality of model transformations, several testing techniques for model transformations have been recently proposed (see [4] for a recent survey). So far, most of the techniques follow a black-box approach (i.e.…”

Using Models of Partial Knowledge to Test Model Transformations

“…Models and transformations have a widespread development in academia and industry because they are generic artifacts to represent complex data structures, constraints, and code abstractions. However, there is little progress in techniques to test transformations [5]. Testing requires the specification of software artifacts called test models that aim to detect faults in model transformations.…”