Using Models of Partial Knowledge to Test Model Transformations

Sen, Sagar; Mottu, Jean-Marie; Tisi, Massimo; Cabot, Jordi

doi:10.1007/978-3-642-30476-7_2

Cited by 19 publications

(21 citation statements)

References 24 publications

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“…Therefore, in the paper, we use a more permissive instance level formalism called partial snapshots (PS) as an additional input or output of DSL validation where certain language constraints are relaxed. During a typical validation run, such a PS While the underlying formalism of PSs is similar to existing approaches [31,35,50,52], we use them in a novel way to assist the DSL validation process, especially, for constructing validation proofs under specific assumptions. In our workflow, a PS can be generalised from a regular (fully specified) instance model by relaxing specific properties identified by the DSL developer, which can guide efficient validation in practically relevant cases.…”

Section: Partial Snapshotsmentioning

confidence: 99%

“…Model extensions using partial models The idea of using partial models, which are extended to valid models during verification also appears in [52,31,35]. These initial hints are provided manually to the verification process, while in our approach, these models are assembled from a previous (failed) verification run by adding partial snapshots of the spurious counterexamples or increase the level of approximation.…”

Section: Validation Of Ocl Enriched Metamodelsmentioning

confidence: 99%

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Formal validation of domain-specific languages with derived features and well-formedness constraints

et al. 2015

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Despite the wide range of existing tool support, constructing a design environment for a complex domain-specific language (DSL) is still a tedious task as the large number of derived features and well-formedness constraints complementing the domain metamodel necessitate special handling. Such derived features and constraints are frequently defined by declarative techniques (such graph patterns or OCL invariants).However, for complex domains, derived features and constraints can easily be formalized incorrectly resulting in inconsistent, incomplete or ambiguous DSL specifications. To detect such issues, we propose an automated mapping of EMF metamodels enriched with derived features and well-formedness constraints captured as graph queries in EMF-IncQuery or (a subset of) OCL invariants into an effectively propositional fragment of first-order logic which can be efficiently analyzed by back-end reasoners.On the conceptual level, the main added value of our encoding is (1) to transform graph patterns of the EMF-IncQuery framework into FOL and (2) to introduce approximations for complex language features (e.g. transitive closure or multiplicities) which are not expressible in FOL. On the practical level, we identify and address relevant challenges and scenarios for systematically validating DSL specifications. Our approach is supported by a tool and it will be illustrated on analyzing a DSL in the avionics domain. We also present initial performance experiments for the validation using Z3 and Alloy as back-end reasoners.

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Section: Partial Snapshotsmentioning

confidence: 99%

Section: Validation Of Ocl Enriched Metamodelsmentioning

confidence: 99%

Formal validation of domain-specific languages with derived features and well-formedness constraints

et al. 2015

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“…However, neither of the above approaches proposes a systematic method to repair the transformation in case counter-examples are produced. Sen et al [SMTC12] use Alloy to create complete versions of partially defined models to use for testing model transformations. This process is reminiscent of the way we use Alloy to generate all extensions of the graph rewrite rule, even though the eventual goal is different.…”

Section: Verifying the Transformationsmentioning

confidence: 99%

A Methodology for Verifying Refinements of Partial Models.

Salay¹,

Chećhik²,

Famelis³

et al. 2015

JOT

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Models are typically used for expressing information that is known at a particular stage in the software development process. Yet, it is also important to express what information a modeler is still uncertain about and to ensure that model refinements actually reduce this uncertainty. Furthermore, when a refining transformation is applied to a model containing uncertainty, it is natural to consider the effect that the transformation has on the level of uncertainty, e.g., whether it always reduces it. In our previous work, we have presented a general approach for precisely expressing uncertainty within models. In this paper, we use these foundations and define formal conditions for uncertainty reducing refinement between individual models and within model transformations. We describe tooling for automating the verification of these conditions within transformations and describe its application to example transformations.

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“…In [20], the generation of input test models must be hand-coded using an imperative language with features for randomly choosing attribute values and association ends. Input models are also hand-crafted in [43], although they are only required to conform to a relaxed version of the input meta-model without mandatory references and general constraints. These so-called partial models are transformed into Alloy and fed into a constraint solver to find valid instances of the original meta-model which can be used for testing.…”

Section: State Of the Artmentioning

confidence: 99%

“…Coverage criteria. Existing black-box testing approaches for model transformations either do not consider coverage criteria [20,43], or support input meta-model coverage (partitioning of attribute values, number of classes and associations, etc.) [13,14,42].…”

Section: State Of the Artmentioning

confidence: 99%

Specification-driven model transformation testing

Guerra

Soeken

2013

Softw Syst Model

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Testing model transformations poses several challenges, among them the automatic generation of appropriate input test models and the specification of oracle functions. Most approaches to the generation of input models ensure a certain coverage of the source meta-model or the transformation implementation code, whereas oracle functions are frequently defined using query or graph languages. However, these two tasks are usually performed independently regardless of their common purpose, and sometimes there is a gap between the properties exhibited by the generated input models and those considered by the transformations.Recently, we proposed a formal specification language for the declarative formulation of transformation properties (by means of invariants, pre-and postconditions) from which we generated partial oracle functions used for transformation testing. Here, we extend the usage of our specification language for the automated generation of input test models by SAT solving. The testing process becomes more intentional because the generated models ensure a certain coverage of the transformation requirements. Moreover, we use the same specification to consistently derive both the input test models and the oracle functions. A set of experiments is presented, aimed at measuring the efficacy of our technique.

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Using Models of Partial Knowledge to Test Model Transformations

Cited by 19 publications

References 24 publications

Formal validation of domain-specific languages with derived features and well-formedness constraints

Formal validation of domain-specific languages with derived features and well-formedness constraints

A Methodology for Verifying Refinements of Partial Models.

Specification-driven model transformation testing

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