Textual Analysis for Code Smell Detection
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The negative impact of smells on the quality of a software systems has been empirical investigated in several studies. This has recalled the need to have approaches for the identification and the removal of smells. While approaches to remove smells have investigated the use of both structural and conceptual information extracted from source code, approaches to identify smells are based on structural information only. In this paper, we bridge the gap analyzing to what extent conceptual information, extracted using textual analysis techniques, can be used to identify smells in source code. The proposed textual-based approach for detecting smells in source code, coined as TACO (Textual Analysis for Code smell detectiOn), has been instantiated for detecting the Long Method smell and has been evaluated on three Java open source projects. The results indicate that TACO is able to detect between 50% and 77% of the smell instances with a precision ranging between 63% and 67%. In addition, the results show that TACO identifies smells that are not identified by approaches based on solely structural information.
![C O D E S M E L L S A R E
S Y M P T O M S O F P O O R
D E S I G N O R
I M P L E M E N TAT I O N C H O I S E S
Code Smell
[Martin Fowler]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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Textual Analysis for Code Smell Detection
- 1. Textual Analysis for Code Smell Detection FA B I O PA L O M B A , U N I V E R S I T Y O F S A L E R N O D I B T. U N I M O L . I T / F PA L O M B A I C S E 2 0 1 5 S R C M AY 2 2 , 2 0 1 5 F L O R E N C E , I TA LY
- 2. C O D E S M E L L S A R E S Y M P T O M S O F P O O R D E S I G N O R I M P L E M E N TAT I O N C H O I S E S Code Smell [Martin Fowler]
- 3. C O D E S M E L L S A R E M O R E C H A N G E - A N D FA U LT- P R O N E N E S S C O D E S M E L L S I N C R E A S E S M A I N T E N A N C E C O S T S Khomh et. al - EMSE 2012 Banker et. al - Communications of the ACM 1993 C O D E S M E L L S H I N D E R C O M P R E H E N S I B I L I T Y Abbes et. al - CSMR 2011
- 4. S E V E R A L A P P ROAC H E S H AV E B E E N P RO P O S E D, E X P L O I T I N G D I F F E R E N T K I N D O F I N F O R M AT I O N S T R U C T U R A L I N F O R M AT I O N H I S T O R I C A L A N A LY S I S
- 5. I S I T P O S S I B L E T O D E T E C T S M E L L S U S I N G C O N C E P T U A L I N F O R M AT I O N ?The Third Dimension
- 6. T H E C A S E O F L O N G M E T H O D D E T E C T I O N TACO - Textual Analysis for Code Smell Detection “A Long Method as a method in which there is the implementation of a main functionality together with auxiliary functions that should be managed in different methods.” [Martin Fowler]
- 7. TACO - Textual Analysis for Code Smell Detection T H E C A S E O F L O N G M E T H O D D E T E C T I O N method mi
- 8. method mi method blocks extract blocks T H E C A S E O F L O N G M E T H O D D E T E C T I O N TACO - Textual Analysis for Code Smell Detection
- 9. method blocks pruned method blocks extract identifiers extract comments extract blocks T H E C A S E O F L O N G M E T H O D D E T E C T I O N TACO - Textual Analysis for Code Smell Detection method mi
- 10. similarity matrix method blocks pruned method blocks compute similarity extract identifiers extract comments extract blocks T H E C A S E O F L O N G M E T H O D D E T E C T I O N TACO - Textual Analysis for Code Smell Detection method mi
- 11. similarity matrix method blocks pruned method blocks compute similarity extract identifiers extract comments I F E X I S T B L O C K S W I T H S I M I L A R I T Y < T H E N A L O N G M E T H O D I S D E T E C T E D extract blocks t T H E C A S E O F L O N G M E T H O D D E T E C T I O N TACO - Textual Analysis for Code Smell Detection method m
- 12. T H E C A S E O F L O N G M E T H O D D E T E C T I O N - C A S E S T U D Y TACO - Textual Analysis for Code Smell Detection Apache Cassandra Apache Xerces Eclipse Core
- 13. TACO - Textual Analysis for Code Smell Detection Apache Cassandra Apache Xerces Eclipse Core Precision Recall F-Measure T H E C A S E O F L O N G M E T H O D D E T E C T I O N - C A S E S T U D Y
- 14. TACO - Textual Analysis for Code Smell Detection Apache Cassandra Apache Xerces Eclipse Core Precision Recall F-Measure Compared with DECOR approach [Moha et al.] T H E C A S E O F L O N G M E T H O D D E T E C T I O N - C A S E S T U D Y
- 15. TACO - Textual Analysis for Code Smell Detection Apache Cassandra Apache Xerces Eclipse Core Precision Recall F-Measure Compared with DECOR approach [Moha et al.] T H E C A S E O F L O N G M E T H O D D E T E C T I O N - C A S E S T U D Y 63% 51% DECOR TACO OVERALL F-MEASURE OVERALL F-MEASURE
- 16. TACO - Textual Analysis for Code Smell Detection Apache Cassandra Apache Xerces Eclipse Core Precision Recall F-Measure Compared with DECOR approach [Moha et al.] TACO is highly complementary with respect to DECOR on 2 systems analyzed T H E C A S E O F L O N G M E T H O D D E T E C T I O N - C A S E S T U D Y 63% 51% DECOR TACO OVERALL F-MEASURE OVERALL F-MEASURE
- 17. A P R AT I C A L E X A M P L E TACO - Textual Analysis for Code Smell Detection Method: findTypesAndPackages() Goal: Discover the classes and the packages of a given project Class: CompletionEngine - Eclipse Core
- 18. TACO - Textual Analysis for Code Smell Detection Method: findTypesAndPackages() Goal: Discover the classes and the packages of a given project This method has 65 lines of code Class: CompletionEngine - Eclipse Core A P R AT I C A L E X A M P L E
- 19. TACO - Textual Analysis for Code Smell Detection Method: findTypesAndPackages() Goal: Discover the classes and the packages of a given project This method has 65 lines of code A S TAT I C A P P R O A C H C A N N O T D E T E C T A L O N G M E T H O D Class: CompletionEngine - Eclipse Core A P R AT I C A L E X A M P L E
- 20. TACO - Textual Analysis for Code Smell Detection Class: CompletionEngine - Eclipse Core Method: findTypesAndPackages() Goal: Discover the classes and the packages of a given project This method has 65 lines of code A S TAT I C A P P R O A C H C A N N O T D E T E C T A L O N G M E T H O D But the method manages more than one responsibility I T A C T U A L LY I S A L O N G M E T H O D ! A P R AT I C A L E X A M P L E
- 21. I S I T P O S S I B L E T O D E T E C T S M E L L S U S I N G C O N C E P T U A L I N F O R M AT I O N !The Third Dimension YES, IT IS
- 22. S U M M A R I Z I N G TACO - Textual Analysis for Code Smell Detection Textual Analysis is useful for smell detection
- 23. Textual Analysis is useful for smell detection Is TACO suitable for detectingother smells? TACO - Textual Analysis for Code Smell Detection What about a hybrid technique for detecting smells? C O M I N G S O O N …
- 24. Textual Analysis for Code Smell Detection FA B I O PA L O M B A , U N I V E R S I T Y O F S A L E R N O D I B T. U N I M O L . I T / F PA L O M B A I C S E 2 0 1 5 S R C M AY 2 2 , 2 0 1 5 F L O R E N C E , I TA LY