Towards an Automated Fault Localizer while Designing Meta-models Adel - - PowerPoint PPT Presentation

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Dec 07, 2023 318 likes •594 views

Towards an Automated Fault Localizer while Designing Meta-models Adel Ferdjoukh and Jean-Marie Mottu MDEbug@MODELS 2018, Copenhagen (Kbenhavn) null Motivation Automated fault localization Tooling Ideas for improving Conclusion Synopsis 1

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Towards an Automated Fault Localizer while Designing Meta-models Adel Ferdjoukh and Jean-Marie Mottu

MDEbug@MODELS 2018, Copenhagen (København)

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Synopsis

1 Motivation 2 Automated fault localization 3 Tooling 4 Ideas for improving 5 Conclusion

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

1. Motivation

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Validity of meta-models

general idea

Ensure the validity of meta-models & help meta-model designers

wished features

1 Localize problems in faulty meta-models 2 Give feedback to designers 3 Propose corrections

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

meta-model validation

Validity of meta-models

Generate valid instances using model finders

Characteristics of model finders

1 Automated 2 Many models 3 Meaningful and Diverse

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Validation with Grimm

Grimm

A tool for model generation and meta-model validation

Validation with Grimm

1 Design a new meta-model 2 Ask for instances 3 Inspect and correct 4 Back to 2

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Validation with Grimm

Grimm

A tool for model generation and meta-model validation

Validation with Grimm

1 Design a new meta-model 2 Ask for instances 3 Inspect and correct (manual task) 4 Back to 2

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Steps for model generation

steps for model generation

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Steps for model generation

detection far from origin

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Steps for model generation

focus for current work

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

2. Automated fault localization

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Proposition

Automated fault localization

Static analysis of meta-model
Check the consistency of generation parameters
Precise localization of errors

Systems of Linear Inequalities

Translate a meta-model and generation parameters into SLI
Write checking algorithms
Give fixing propositions

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

From Ecore to SLI

#House ≤ #Room

#Room ≤ 5 × #House

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

From Ecore to SLI

#House ≤ #Room

#Room ≤ 5 × #House

3H & 4R
2H & 1R

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

From Ecore to SLI

Translated Ecore elements

1 Simple references 2 Compositions 3 Eopposite references 4 Inheritance combined with 1,2 and 3

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Checking the SLI and propositions

Checking the SLI

Each Inequality is checked using the candidate values
Detect all faults in 1 shot

Fixing propositions

Detected anomaly
Help propositions (manual fixing)

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

3. Tooling

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Automated Fault Localization

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

TIWIZI tool

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

4. Ideas for improving

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Meta-model & partial solutions

Meta-model validity

Solve the SLI to propose solutions (intervals of values)
Detect meta-model anomalies

Partial solutions

1 Users give some CVs (not all classes) 2 Solve the SLI 3 Complete remaining CVs

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Global fixing propositions

Current solution

Fixing propositions concern one reference (or two classes).

Improvement idea

Learn more complex propositions (eg. 3 classes at once)
Auto-fix generation

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

5. Conclusion

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Motivation Automated fault localization Tooling Ideas for improving Conclusion

Conclusion

Summary

Approach for assisting meta-model designers

Contributions

Translation of Ecore meta-models into SLI
Automated fault localization during instantiation.
Precise fixing propositions

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