A Deductive Approach for Fault Localization in ATL Model Transformations

Int J Softw Tools Technol Transfer

2018

Self Cite

Model-driven engineering (MDE) is increasingly accepted in industry as an effective approach for managing the full life cycle of software development. In MDE, software models are manipulated, evolved and translated by model transformations (MT), up to code generation. Automatic deductive verification techniques have been proposed to guarantee that transformations satisfy correctness requirements (encoded as transformation contracts). However, to be transferable to industry, these techniques need to be scalable and provide the user with easily accessible feedback. In MT-specific languages like ATL, we are able to infer static trace information (i.e. mappings among types of generated elements and rules that potentially generate these types). In this paper we show that this information can be used to decompose the MT contract and, for each subcontract , slice the MT to the only rules that may be responsible for fulfilling it. Based on this contribution, we design a fault localization approach for MT, and a technique to significantly enhance scalability when verifying large MTs against a large number of contracts. We implement both these algorithms as extensions of the VeriATL verification system, and we show by experimentation that they increase its industry-readiness.

Section: Introductionsupporting

confidence: 71%

Section: Motivating Examplementioning

confidence: 95%

Slicing ATL model transformations for scalable deductive verification and fault localization

Int J Softw Tools Technol Transfer

2018

Self Cite

“…We manually checked that our approach is complete for our evaluation, and identify two possible sources of incompleteness: (a) the limits of the underlying SMT solver [21]. (b) unsuccessful application of natural deduction rules by the designed automated proof strategy [14]. We plan to design more natural deduction rules for ATL and a smarter automated proof strategy to contribute to the completeness of the approach.…”

Section: Discussionmentioning

confidence: 99%

“…To alleviate the cognitive load on developers investigating why a transformation is incorrect, in previous work we have provided VeriATL with fault localization capabilities by using natural deduction and program slicing [14]. Specifically, we proposed a set of sound natural deduction rules for the ATL language, including rules for propositional logic such as ∀ i (introduction rule for ∀), and ∨ e (elimination rule for ∨) [16], but also transformation-specific rules based on the concept of static trace (i.e.…”

Section: Localizing the Faultmentioning

confidence: 99%

Incremental Deductive Verification for Relational Model Transformations

2017 IEEE International Conference on Software Testing, Verification and Validation (ICST)

2017

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In contract-based development of model transformations, continuous deductive verification may help the transformation developer in early bug detection. However, because of the execution performance of current verification systems, re-verifying from scratch after a change has been made would introduce impractical delays. We address this problem by proposing an incremental verification approach for the ATL modeltransformation language. Our approach is based on decomposing each OCL contract into sub-goals, and caching the sub-goal verification results. At each change we exploit the semantics of relational model transformation to determine whether a cached verification result may be impacted. Consequently, less postconditions/sub-goals need to be re-verified. When a change forces the re-verification of a postcondition, we use the cached verification results of sub-goals to construct a simplified version of the postcondition to verify. We prove the soundness of our approach and show its effectiveness by mutation analysis. Our case study presents an approximate 50% reuse of verification results for postconditions, and 70% reuse of verification results for sub-goals. The user perceives about 56% reduction of verification time for postconditions, and 51% for sub-goals.

“…Cheng and Tisi address usability aspects of automatic theorem proving for RMT, e.g. fault localization [12], scability [14] and incrementality [13]. However, interactive theorem proving has shown to be necessary for certifying RMTs for complex properties.…”

Section: Related Workmentioning

confidence: 99%

Certifying a rule-based model transformation engine for proof preservation

Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems

Hotonnier

2020

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Executable engines for relational model-transformation languages evolve continuously because of language extension, performance improvement and bug fixes. While new versions generally change the engine semantics, end-users expect to get backward-compatibility guarantees, so that existing transformations do not need to be adapted at every engine update. The CoqTL model-transformation language allows users to define model transformations, theorems on their behavior and machinechecked proofs of these theorems in Coq. Backward-compatibility for CoqTL involves also the preservation of these proofs. However, proof preservation is challenging, as proofs are easily broken even by small refactorings of the code they verify. In this paper we present the solution we designed for the evolution of CoqTL, and by extension, of rule-based transformation engines. We provide a deep specification of the transformation engine, including a set of theorems that must hold against the engine implementation. Then, at each milestone in the engine development, we certify the new version of the engine against this specification, by providing proofs of the impacted theorems. The certification formally guarantees end-users that all the proofs they write using the provided theorems will be preserved through engine updates. We illustrate the structure of the deep specification theorems, we produce a machine-checked certification of three versions of CoqTL against it, and we show examples of user theorems that leverage this specification and are thus preserved through the updates. CCS CONCEPTS • Theory of computation → Logic; • Software and its engineering → Software notations and tools.