1) The document presents an approach for suggesting refactorings to correct design defects (DDs), specifically the "Blob" defect, using relational concept analysis (RCA). 2) RCA is used to identify cohesive sets of methods and fields in classes affected by Blob defects. These cohesive sets suggest refactorings like moving methods/fields to new or existing classes. 3) An experimental study on four open-source programs evaluated the approach, finding an average precision of 57% for suggested refactorings that improved class structure and design. The approach could potentially be generalized to other types of DDs.

1. Refactorings of Design Defects using
Relational Concept Analysis
Naouel Moha, Amine Mohamed Rouane Hacene,
Petko Valtchev, and Yann-Gaël Guéhéneuc
LORIA, France
DIRO, University of Montréal, Canada
LATECE, Université du Québec à Montréal, Montréal, Canada
ICFCA’08
Montréal (Qc), Canada, February 25-28, 2008

2. Context
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3. Context
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4. Context
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5. Context: Overall Process
Textual descriptions
of design defects
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Rules Refactorings
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Classes having Better
design defects Design
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6. Context: Overall Process
Textual descriptions
of design defects
1 S 3
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Rules Refactorings
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Classes having Better
design defects Design
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7. Context: Overall Process
1-2. Specification and Detection of DDs
More and more tools and techniques
Actively researched area
Method DECOR (Defect dEtection for CORrection) [Moha 06]
3. Suggestion
3 S ti
Manual identification of the modifications
Time-, resource-consuming, error-prone activity
, g, p y
4. Correction
Refactorings
g
Technique used to change “the internal structure of software to make it
easier to understand and cheaper to modify without changing its
observable behavior”
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8. What Kind of Defects ?
Design Patterns are “good” solutions to recurring design problems
Design Defects (DDs)
are “bad” solutions to recurring problems, Antipatterns [Brown 98]
hinder d
hi d development and maintenance by making programs h d t
l t d i t b ki harder to
comprehend and/or evolve
DDs of interest: infected by low cohesion and high coupling
Cohesion: how closely the methods are related to the variables in
the class
Coupling: the degree of its reliance on services provided by other
classes
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9. What Kind of Defects ?
An example of DDs [Brown 98]
Blob (God Class)
“ Procedural-style design leads to one object with a
lion’s share of the responsibilities while most other
objects only hold data or execute simple processes ”
Large controller class
Many fields and methods with a low cohesion
High coupled with the data stored in
associated data classes
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10. An Example
Blob
Before
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11. An Example
How t correct th d f t ?
H to t the defect
Before After
Large and complex class Large class becomes less complex
Small data classes Data classes gain more behaviour
Not object-oriented More object-oriented style
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12. An Example
Redistribute l
R di t ib t class members among existing classes ( ith possibly
b i ti l (with ibl
new classes) to increase cohesion and–or decrease coupling
Before After
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13. Contribution
Suggestion
RCA [Rouane 07, Ph.D. Thesis]
Extension of FCA to relational d
E i f l i l data
Models the inter-object links and infers description logics role like
relations between concepts
RCA provides a suitable framework for clustering individuals along
the properties they share and their links with other individuals
Identify methods that share common fields and methods that call
common methods cohesive sets low coupled
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14. Contribution
Suggestion
RCA [Rouane 07, Ph.D. Thesis]
Extension of FCA to relational d
E i f l i l data
Models the inter-object links and infers description logics role like
relations between concepts
RCA provides a suitable framework for clustering individuals along
the properties they share and their links with other individuals
Identify methods that share common fields and methods that call
common methods cohesive sets low coupled
«D
Develop an automated approach f suggesting d f t
l t t d h for ti defect-
correcting refactorings using RCA »
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15. An Example
How t correct th d f t ?
H to t the defect
Before After
Large and complex class Large class becomes less complex
Small data classes Data classes gain more behaviour
Not object-oriented More object-oriented style
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16. An Example
How t correct th d f t ?
H to t the defect
Blob Cohesive Sets
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17. An Example
How t correct th d f t ?
H to t the defect
I = {W-borrow_date_Book, W-return_date_book}
E = {}
I = {‘check_Availability_Book()’}
E = {check_Availability_Book()}
I = {call:c4}
E = {}
I = {‘borrow_Book()’} I = {‘reserve_Book()’, W-reserved_book}
E = {borrow_Book()} E = {reserve_Book()}
Lattice Cohesive Set
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18. An Example
How t correct th d f t ?
H to t the defect
Cohesive Sets After Refactoring *
* Move Method Mode Field, Create Class
Method, Field
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19. Suggestion
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20. Suggestion
1. RCF Modeling
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21. Suggestion
2. RCA Al
Algorithms
ith
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22. Suggestion
2. RCA Al
Algorithms
ith
9
I = {W-library opened}
{W library_opened}
E={}
10
I = {‘open_Library()’}
E = {open Library()}
{open_Library()}
7
I = {‘close_Library()’}
E = {close_Library()}
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23. Suggestion
2. RCA Al
Algorithms
ith
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24. Suggestion
2. RCA Al
Algorithms
ith
4
I = {‘check_Availability_Book()’}
E = {check_Availability_Book()}
19
I = {call:c4}
E={}
3 12
I = {‘borrow_Book()’} I = {‘reserve_Book()’,W-reserved_book}
E = {borrow_Book() } E = {reserve_Book()}
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25. Suggestion
3. Interpretation
Cohesive Sets After Refactoring
* Move Method Mode Field, Create Class
Method, Field
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26. Experimental Study
Tooling
PADL to model source code and generate contexts
Galicia to construct and visualize the concept lattices
Experiments
E i t
Goal: evaluate the relevance of the cohesive sets suggested
4 different open-source programs
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27. System Experimental Study
Nb of fields/ Nb of Nb of real
Size (fields +
Blob Class LOC methods cohesive cohesive Precision
methods)
moved sets sets
DHTTransportUDPImpl 2,049 (42+66) 108 (27+32) 59 10 7 70%
V2.3.0.6
Azureus
DHTControlImpl 1,868 (47+80) 127 (35+62) 97 19 11 58%
TRTrackerBTAnnouncerImpl 1,393 (36+47) 83 (24+33) 57 16 5 31%
V0.7.1 V1.4 V1.2.1
LogBrokerMonitor 1,142 (29+105)134 (23+85) 108 31 17 55%
ene Log4j
Category 387 (9+53) 62 (8+44) 52 18 9 50%
IndexReader 236 (7+52) 59 (5+30) 35 4 2 50%
Nutch Luce
QueryParser 829 (36+48) 84 (24+37) 61 13 10 77%
FSNamesystem 710 (24+35) 59 (17+25) 42 18 9 50%
JobTracker 555 (
(22+31) 53
) (
(17+18) 35
) 11 8 73%
Average Precision: 57%
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28. Conclusion
Contribution
an approach that uses RCA to suggest refactorings to correct
certain DDs in particular Blob
DDs,
Validation
4 different programs
Relevant refactorings to improve programs
Future Work
- Generalise to other DDs
- Assess more programs via our approach
- Discuss the suggested refactorings with their developers and
apply them
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29. Questions
Contact: mohanaou@iro.umontreal.ca
http://www-etud.iro.umontreal.ca/~mohanaou
Thanks for your attention !
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