Abstract Model Repair

Chatzieleftheriou, George; Bonakdarpour, Borzoo; Smolka, Scott A.; Katsaros, Panagiotis

doi:10.1007/978-3-642-28891-3_32

Cited by 29 publications

(2 citation statements)

References 14 publications

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“…• Applied model repair [CBSK12], model refinement [PMBM98] and model transformation [BP96] to improve our models. 2 Modelling Syntax and Semantics of an Instruction…”

Section: Main Challenges and Approachesmentioning

confidence: 99%

“…Model fixing was a labour intensive process due to its manual nature, but cross-checking different parts of the models with one another, as well as models extracted from different sources even within the same original document, was useful. Conceptually this was a straightforward application of abstract model repair [CBSK12].…”

Section: Conclusion and Lessons Learntmentioning

confidence: 99%

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Modelling of Language Syntax and Semantics: The Case of the Assembler Compiler.

Zaytsev¹

2020

JOT

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Application of software language technologies, whether analytical, transformational, or generational, in an industrial context is usually a taxing endeavour, with high demands in qualification levels of developers involved in it. Yet, if applied successfully, in the right places and with the right amount of effort, they promise high returns in terms of optimisation, effectiveness, validity and verifiability. In this paper, we report on our experience on writing a compiler for a complex second generation legacy programming language originally intended to be used on a mainframe. The business case for this product deals with companies migrating their software systems off the mainframe to cloud native or PC. Leveraging the documentation, available domain knowledge, several sample projects and a test suite, as well as several proprietary DSLs, we successfully modelled syntax and semantics of hundreds of instructions of that language, to the point of producing a compiler with a very limited group of compiler developers in limited time. The compiler is currently deployed at some of our customers and has received a top technology award from Microsoft.This report is meant to serve as a sample snapshot of how compilers can be built in the industry with software language engineering techniques. Traditional problems of compiler construction such as parsing or code optimisation either did not present a noticeable challenge or did not manifest themselves altogether in the course of this project, but MDE matters such as model transformation, modular design, the use of DSLs and meta-tools, were a constant concern. The focus of the report is in truthful representation of the domain as well as the details of the project, on reflection of the choices that were taken or could have been taken in the meantime, and on lessons learnt during the project.

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“…• Applied model repair [CBSK12], model refinement [PMBM98] and model transformation [BP96] to improve our models. 2 Modelling Syntax and Semantics of an Instruction…”

Section: Main Challenges and Approachesmentioning

confidence: 99%

Section: Conclusion and Lessons Learntmentioning

confidence: 99%

Modelling of Language Syntax and Semantics: The Case of the Assembler Compiler.

Zaytsev¹

2020

JOT

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Model and Program Repair via Group Actions

Attie¹,

Cocke²

2023

Lecture Notes in Computer Science

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Given a textual representation of a finite-state concurrent program $$P$$ P , one can construct the corresponding Kripke structure $$\mathcal {M}$$ M . However, the size of $$\mathcal {M}$$ M can be exponentially larger than the textual size of $$P$$ P . This state explosion can make model checking properties of $$P$$ P via $$\mathcal {M}$$ M expensive or even infeasible. The action of a symmetry group $$G$$ G on $$\mathcal {M}$$ M can be used to produce a smaller Kripke structure $$\overline{\mathcal {M}}$$ M ¯ . Various authors have exploited the direct correspondence between $$\mathcal {M}$$ M and $$\overline{\mathcal {M}}$$ M ¯ to perform model checking. When the structure $$\mathcal {M}$$ M does not satisfy a formula, one can look for a substructure that will satisfy the formula. We call this substructure-repair: identifying a substructure $$\mathcal {N}$$ N of $$\mathcal {M}$$ M that satisfies a given temporal logic formula.In this paper we extend previous work by showing that repairs of $$\overline{\mathcal {M}}$$ M ¯ lift to repairs of $$\mathcal {M}$$ M . In other words, we can repair a computer program $$P$$ P , which exhibits a high degree of symmetry, by repairing the smaller Kripke structure $$\overline{\mathcal {M}}$$ M ¯ and then symmetrizing the corresponding program. To do this we arrange the substructures of $$\mathcal {M}$$ M and $$\overline{\mathcal {M}}$$ M ¯ into substructure lattices that are ordered by substructure inclusion. We show that the substructures of $$\mathcal {M}$$ M preserved by $$G$$ G form a (sub)lattice that maps to the substructure lattice of $$\overline{\mathcal {M}}$$ M ¯ . When restricted to the lattice of substructures of $$\mathcal {M}$$ M that are “maximal” with the action of $$G$$ G on $$\mathcal {M}$$ M , the above map is a lattice isomorphism.These results enable us to repair $$\overline{\mathcal {M}}$$ M ¯ and then to lift the repair to $$\mathcal {M}$$ M . In cases where a program has a high degree of symmetry, such as in many concurrent programs, we can repair the program by repairing the small Kripke structure $$\overline{\mathcal {M}}$$ M ¯ .

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