Clone Detection for Graph-Based Model Transformation Languages

Clone Detection for Graph-Based Model Transformation Languages

Daniel Strüber1, Jennifer Plöger1, Vlad Acrețoaie2

1 Philipps-Universität Marburg, Germany2 Technical University of Denmark, Lyngby, Denmark

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Common wisdom: software clones are a bad practice.

Daniel Strüber, Jennifer Plöger, Vlad Acrețoaie:Clone Detection for Graph-Based Model Transformation Languages

“Number one in the stinkparade is duplicated code.If you see the same codestructure in more thanone place, you can be surethat your program will bebetter if you find a way tounify it.”[Fowler 2002, p. 63]

© Images: Addison-Wesley Professional,Author‘s website

• Clone: A copied piece of software,modified to fit for a new purpose.

• Makes up large percentage of allcode: 15-25% in embedded SW

• Related to quality issues• Error-prone• Dead code• Inflated code base

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Common wisdom: software clones are a bad practice.

p

p‘“clone“

copy &modify


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Motivations forcloning in practice

• Abstractions havetheir own cost/risk

• Easy exploration

• Sometimesunavoidable!

[WCRE’06/ESE’08]

Software clones are a bad practice: really?

→ In fact, there’s a trade-off.


© Images: Author‘s websites

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Models Transformations Source Code

Clones in Model-Driven Engineering


publicclass { }

publicclass { }

publicclass { }

publicclass { }

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• Multiple rule variants: Reusemechanisms rarely available,cloning is a common paradigm• Error-prone• Leads to large rule sets• Performance bottlenecks

• A clone detection toolto address these issuesis not available yet• Many promising use-cases!

Clones in Graph-Based Model Transformations


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Agenda

• Clones in Model Transformations

• Use-Cases & Requirements

• Customizing Existing Techniques

• Evaluation


Refactoring Clone management Smart IDEs

Qualityassessment

Performanceoptimization

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Use-Cases for Clone Detection Techniques


© Images: Jens Mortensen/NY Times, Sarimin, Kevin Thompson, David Robertson, QALogic

http://www.nytimes.com/2012/02/12/magazine/rubiks-cube.html?_r=0

https://play.google.com/store/apps/details?id=com.oscarperdanakusuma.filemanager&hl=de

https://dribbble.com/kevinthompson

http://www.hooktraffic.com/

http://www.qalogic.in/

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Use case 1: Refactoring

DiamCirc

Tri

Replace clones with a reuse mechanism

• Reuse mechanisms: annotative vs. composition-based

• Manual refactoring tedious: 100s of rules! Calls for automation [Strüber et al. FASE16]


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Use case 2: Clone Management

Leave clones as is & propagate changes automatically

• Useful if refactoring is unavailable/undesirable

• Related work on code clones[Nguyen et al. TSE12, Narasimhan et al. ASE15]

Management Tool

monitors

synchronizesedits


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Use case 3: Smart IDEs

monitors

Smart IDE

monitors &recommends

edits


Can support transformation developers

• Introduce abstractions

• Reuse existing elements

• Auto-completion

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Use case 4: Quality assessment

QAToolhow many

clones?

Assess transformations and whole languages

• Useful for QA teams, teachers, language designers

• Can identify new design patterns


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Use case 5: Performance optimization

Large number of rules: performance slows down

• 1000s of rules can take hours to execute

• Variability-aware execution engine [Strüber et al., FASE15]

Execution engine

…


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Pattern-based

Completeness

Performance

Suitable scope

Tool integration

Clone detection for graph-based MT: requirements


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Pattern-based

Completeness

Performance

Suitable scope

Tool integration



Rules specify patterns →Clones are common sub-patterns

Clone

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Pattern-based

Completeness

Performance

Suitable scope

Tool integration



Reported clones should becomplete rather than partial

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Pattern-based

Completeness

Performance

Suitable scope

Tool integration



Mining common graph patterns is NP-hard

Generic pattern miningtools do not scale

© Image: W RCheswick/ Bell Labs

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Pattern-based

Completeness

Performance

Suitable scope

Tool integration



May require to find clones

• inside one rule

• across multiple rules

• across whole rule sets

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Pattern-based

Completeness

Performance

Suitable scope

Tool integration



Should be integrated withexisting MT tools

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Pattern-based

Completeness

Performance

Suitable scope

Tool integration


Hard requirement, Soft requirement, Not required


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Adapt model clone detection tools toaddress the requirements of MT CD

• Two suitable ones:

• ConQAT [Deissenboeck et al., WSC 2010]

• eScan [Pham et al., ICSE 2009]

• Both introduced for Simulink models

• accuracy vs. performance trade-off


Groups of clonefragments

eScan

Labeledgraph

a priori algo

Clusters ofClone pairs

Labeledgraph

ConQAT

heuristics

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Adaptation of existing techniques

Cloneconverters

Rule clones

Ruleconverters

Rules


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Evaluation

Materials

• 2 rule sets of 50-60 rules• Edit operation recognition [Bürdek 2015]• Model constraint translation [Arendt 2014]• In both cases, 8-12 subsets

Set-up

• Studied if eScan, ConQAT,and our custom detectorScanQAT satisfy therequirements

• Applied search to the whole rule setsand each group


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Results

Pattern-based

Completeness

Performance

Suitable scope

Tool integration

ConQAT ScanQAT eScan

D = Ensured by design

D D D

I I I

I I I

D Dat leastfor subsets

1-10secrule sets:memoryoverflow

rule sets:memoryoverflow


I = Enabled by our implementation

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Tool support

DEMO


Refactoring Clone management Smart IDEs

Qualityassessment

Performanceoptimization

Usecases:

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Contributions:• Five use-cases & reqs• Adaptation of available

techniques• Evaluation on real rules

Future Work:• Incremental model CD• CD for other language

paradigms• Large-scale evaluation

Beefing up model clone detectors for graph-based MT clone detection


Science

Clone Detection for Graph-Based Model Transformation Languages