Slides for the paper "Revisiting the Relationship Between Code Smells and Refactoring" in the Proceedings of the 24th IEEE International Conference on Program Comprehension (ICPC 2016), Austin, TX, USA, May 2016

1. REVISITING
THE RELATIONSHIP BETWEEN
CODE SMELLS AND
REFACTORING
Norihiro Yoshida (Nagoya Univ.)
Tsubasa Saika (Osaka Univ.)
Eunjong Choi (NAIST)
Ali Ouni (Osaka Univ.)
Katsuro Inoue (Osaka Univ.)
1

2. Code smell and Refactoring
Fowler [1] introduced a correspondence
relationship between
• Smell type
• Refactoring to remove its instance
Smell type Common Refactoring
Feature Envy Extract Method, Move Method, Pull-
up Method, Move Field
Data Class Move Method, Encapsulate Field,
Encapsulate Collection
[1] M. Fowler: “Refactoring: Improving the Design of Existing Code”,
Addison-Wesley Professional, 1999.
2

3. Motivation
• Bavota et al.’s investigation [2]
“40% of the refactorings was performed on classes
affected by smells, but just 7% removed the smell.”
• It does not align with Fowler’s book.
3
[2] G. Bavota, et al.: “An experimental
investigation on the innate relationship between quality and refactoring,”
Journal of Systems and Software, 2015.
Question
Why does refactoring rarely remove code smell?

4. Applied refactoring patterns rarely correspond to
types of the code smell.
4
In order to test the hypothesis, we empirically
investigate three OSS projects.
An Overview of This Study
Hypothesis
This study

5. Data we analyzed
- Refactoring instances
Refactoring instances in Bavota et al.’s dataset [3]
• They manually validated the instances.
5
Period Releases Classes Refactoring
instances
Xerces-J Oct. ‘99 - Nov. ‘10 34 19,567 6,052
ArgoUML Oct. ‘02 - Dec. ‘11 12 43,686 3,423
Ant Jan. ‘00 - Dec. ‘10 18 22,768 1,493
[3] G. Bavota et al.: “When does a refactoring induce bugs? an empirical study,”
In Proc. of SCAM 2012.

6. Data we analyzed
- Code smells
6
Code Smells #Classes
BlobClass 692
DataClass 1,679
DistortedHierarchy 8
GodClass 1,294
RefusedParentBequest 538
SchizophrenicClass 311
TraditionBreaker 249
Total 4,771
Code Smells #Methods
BlobOperation 4,610
DataClumps 1,402
ExternalDuplication 1,656
FeatureEnvy 1,364
IntensiveCoupling 1,290
InternalDuplication 2,218
MessageChains 31
ShotgunSurgery 65
SiblingDuplication 1,956
Total 14,592
We detected code smells from each release
version by inFusion.

7. List of corresponding refactoring patterns
• We made a list of the corresponding refactoring
patterns for each type of code smell.
• Referred the following books:
• M. Fowler: “Refactoring: Improving the Design of Existing Code”,
Addison-Wesley Professional, 1999.
• M. Lanza and R. Marinescu, “Object-Oriented Metrics in
Practice”, Springer-Verlag, 2005.
• Investigated the effectiveness of each refactoring
pattern for each type of code smell manually.
• Once an instance showed the effectiveness, we regarded that
the pattern corresponds to the type of code smell.
7

8. Investigation result
- Class-level code smell
Code Smells
#Refactored
Classes
#Classes
w/ Corresponding Refactorings
Ratio
BlobClass 210 180 85.7%
DataClass 43 8 18.6%
DistortedHierarchy 4 0 0.0%
GodClass 284 54 19.0%
RefusedParentBequest 40 7 17.5%
SchizophrenicClass 34 9 26.5%
TraditionBreaker 15 3 20.0%
Total 630 261 26.8%
8
Only 26.8% were refactored by corresponding patterns.
Only BlobClass was frequently refactored
by corresponding patterns.

9. Investigation result
- Method-level code smell
Code Smells
#Refactored
method
#Methods
w/ Corresponding Refactorings
Ratio
BlobOperation 436 180 68.8%
DataClumps 50 8 0.0%
ExternalDuplication 69 0 4.3%
FeatureEnvy 86 54 10.5%
IntensiveCoupling 107 7 22.4%
InternalDuplication 164 9 17.1%
MessageChains 4 3 0.0%
ShotgunSurgery 3 0 0.0%
SiblingDuplication 147 31 21.1%
Total 1,066 395 16.0%
9
Only 16.0% were refactored by corresponding patterns.
Only BlobOperation was frequently refactored
by corresponding patterns.

10. Discussion
10
Applied refactoring patterns rarely correspond to
types of the code smell.
Hypothesis
Only 16.0-26.8% of instances corresponded to
types of the code smell.
Investigation Result
The hypothesis is true!

11. Conclusion
11
Answer
Since corresponding patterns are rarely applied
to code smells, refactoring rarely removes them.
Question
Why does refactoring rarely remove code
smell?

12. Future Work
Replicate this study using the following
datasets / approaches.
• Other datasets of code smells [2]
• Other approach to detecting code smells [4]
• Other aproach for detecting refactoring
instances [5].
12
[2] G. Bavota, et al.: “An experimental
investigation on the innate relationship between quality and refactoring,”
Journal of Systems and Software, 2015.
[4] F. Palomba, et al.: “Mining version histories for detecting code smells,” IEEE
Trans. Softw. Eng., 2015.
[5] Z. Xing and E. Stroulia, “Refactoring detection based on UMLDiff
change-facts queries,” in Proc. of WCRE 2006.