Class Model Normalization Outperforming Formal Concept Analysis approaches with AOC-posets

Class Model Normalization

Outperforming Formal Concept Analysis approaches with AOC-posets

A. Miralles, G. Molla

Tetis/IRSTEA, France

M. Huchard, C. Nebut

LIRMM, CNRS & Université de Montpellier, France

L. Deruelle, M. Derras

Berger Levrault, France

12th International Conference on Concept Lattices and their Applications Clermont-Ferrand, 2015 october, 13-16

Context: Information systems, software engineering

Class models, inheritance hierarchies

I Capture domain knowledge

I Focus on classification and reuse Normal form

I No redundancy

I All abstractions are created

I All specialization links are present

I Most compact structure with these properties

Context

Existing approaches

I Formal Concept Analysis (FCA) (Ganter and Wille, 1999) Galois lattices (Barbut and Monjardet, 1970)

I Flatcharacteristics (Godin et al., 1993)

I Hierarchicalcharacteristics (Godin et al., 1993)

I Relational Concept Analysis (RCA) (Huchard et al., 2007)

I Reifiedcharacteristics (Roume et al., 2004)

I ExploratoryRCA (Dolques et al., 2015; Miralles et al., 2015)

I Question: Difference in using concept latticesversus

AOC-posets in class model normalization with RCA from the designer point of view (effort in post-analysis)

Normalization: initial class model

Normalization: class model in normal form

Relational Concept Analysis for class model normalization

Relational Context Family Dataset

I Several entity categories (OA-contexts): classes, attributes, operations, roles, associations, etc.

I Relations between entities (OO-contexts): hasAttribute, hasRole, hasOperation, hasTypeEnd, etc.

Relational Concept Analysis for class model normalization

Principle

I Build one concept lattice for each entity category

I Iterate on lattice construction and integration of relational attributes (encoding OO-contexts) in OA-contexts

I Until a fix-point or a chosen step

I Results can be observed at any step (in our case study: step 6)

Object-Attribute contexts

Kclass RainGauge Anemometer Rainfall Wind RainReport

Krole measuredRainfall measuredWind storedRainfall

RG::measuredRainfall ×

RR::storedRainfall ×

A::measuredWind ×

Koperation print MC MCWA MCWSWD PstoredRF

RR::print × ×

R::printinfo × × ×

W::printinfo × × ×

Kattribute tubeHeight measureInterval precision measuringDate codeQuality waterAmount windStrength windDirection period number int real

RG::tubeHeight ×

A::measureInterval ×

A::precision ×

R::measuringDate ×

W::measuringDate ×

R::codeQuality × × ×

W::codeQuality × × ×

R::waterAmount ×

W::windStrength ×

W::windDirection ×

RR::period ×

Object-Object contexts

hasAttribute RG::tubeHeight A::measureInterval A::precision R::measuringDate W::measuringDate R::codeQuality W::codeQuality R::waterAmount W::windStrength W::windDirection RR::period

RainGauge ×

Anemometer × ×

Rainfall × × ×

Wind × × × ×

RainReport ×

hasRole RG::measuredRainfall RR::storedRainfall A::measuredWind

RainGauge ×

Anemometer ×

Rainfall Wind

RainReport ×

hasOperation RR::print R::printinfo W::printinfo RainGauge

Anemometer

Rainfall ×

Wind ×

RainReport ×

hasTypeEnd Rainfall Wind

RG::measuredRainfall ×

RR::storedRainfall ×

A::measuredWind ×

All concept lattices

Detail on class lattice and attribute lattice

Concept lattice

WithO the described entities, Athe characteristics

#concepts: in lattice≤2min(|O|,|A|)

Concept_Device_1

recommendedHeight windVaneDimension Concept_Device_3

Concept_Device_6 vaneType VaneAnemometer

Concept_Device_7 plateDimension PlateAnemometer

Concept_Device_4

Concept_Device_8 tubeLength PitotAnemometer Concept_Device_5

cupNumber CupAnemometer

Concept_Device_2 Concept_Device_0

Classes empty of attribute and method declarations

AOC-poset

WithO the described entities, Athe characteristics

#concepts: in AOC-poset≤ |O|+|A|

Concept_Device_1 recommendedHeight

Concept_Device_5 cupNumber CupAnemometer

Concept_Device_6 vaneType VaneAnemometer

windVaneDimension Concept_Device_3

Concept_Device_8 tubeLength PitotAnemometer Concept_Device_7

plateDimension PlateAnemometer

Some domain concepts may be lost, but no class empty of declaration

Question

Difference in using concept latticesversus AOC-posets in class model normalization with RCA from the designer point of view (effort in post-analysis)

Case study: Concept lattice versus AOC-poset

Assessing the reduction in #concepts

UML Models #classes #attrib. #roles #assoc. #op. #elements

Pesticides V00 34 118 45 45 12 254

Pesticides V01 66 149 51 51 14 331

Pesticides V02 75 119 39 39 12 284

Pesticides V03 73 121 35 35 12 276

Pesticides V04 108 206 61 61 17 453

Pesticides V05 136 270 74 74 17 571

Pesticides V06 134 266 74 74 17 565

Pesticides V07 114 171 62 62 17 426

Pesticides V08 121 169 65 65 17 437

Pesticides V09 126 174 65 65 5 435

Pesticides V10 126 174 66 66 5 437

Pesticides V11 170 183 86 86 5 530

Pesticides V12 172 186 90 90 5 543

Pesticides V13 170 185 94 94 5 548

Pesticides V14 171 186 95 95 5 552

Java Models #classes #attrib. #roles #assoc. #elements

Chapter dist C01 37 95 36 36 204

Chapter dist C02 112 290 187 187 776

Chapter dist C04 223 829 496 496 2444

Chapter dist C08 282 1633 1032 1032 3979

Meta-model used in case study

Dashed relation useless in Java

Results on Pesticides models: Lattice

34 to 172 classes (254 to 571 model elements) Step 6: 165% to253%of new classes

→208 to 344potential new factorization classes to be analyzed

Results on Pesticides models: AOC-poset

34 to 172 classes (254 to 571 model elements) Step 6: 52% to132%of new classes

→89 to45 potential new factorization classes to be analyzed

Results on Pesticides models

#New class concepts in AOC−poset Low variation: between 1 and 6 %

Results on Java models: Lattice

Results on Java models: AOC-poset

Results on Java models

Lattice (S5/6)

#class # model elements # new classes % new classes

Dist 1 37 204 4 11 %

Dist 2 112 776 69 62%

Dist 4 223 2044 2346 1052 %

Dist 8 282 3979 43656 15481 %

AOC-poset (S5/6)

#class # model elements # new classes % new classes

Dist 1 37 204 3 8%

Dist 2 112 776 49 44 %

Dist 4 223 2044 208 93 %

Dist 8 282 3979 453 161 %

Results on Java models

#New class concepts in AOC−poset

Conclusion/Perspectives

Conclusion

I Concept lattices and AOC-posets give two different consistent normal forms from a thematic point of view

I two different UML models

I AOC-posets size is more acceptable for analysis by an expert

I UML models:

I results show that the technique is valuable

I from version to version, the model has been improved by the designer, including natural generalization, explaining low difference between lattice and AOC-poset

I Java models: re-work is needed, the meta-model used seems too complex

I Java enumerations have been introduced as classes which brings extra complexity

Conclusion/Perspectives

Perspectives

I Analyze differences between Concept lattice and AOC-poset from a thematic and UML (with consequences on associations) points of view

I Work on methodological aspects

I Exploration

I Guiding metrics

I Model rebuilding at each step for controlling normalization process (accept/reject/modify)

Questions?

Data: UML Pesticides models (IRSTEA), Java source code (Berger Levrault)

Tools: Objecteering modules¹, RCAexplore², Talend workflow³, Java packages

Ack.: Xavier Dolques, ICube, ENGEES, Strasbourg (RCAexplore)

1http://www.objecteering.com/

2http://dolques.free.fr/rcaexplore.php

3http://www.talend.com/