Code smells are characteristics of the software that may indicate a code or design problem that can make software hard to evolve and maintain. Detecting and removing code smells, when necessary, improves the quality and maintainability of a system. Code smells have been defined in [5], and different detection tools have been developed, each one characterized by particular features and providing often different results. Usually detection techniques are based on the computation of a particular set of combined metrics, or standard object-oriented metrics [8] or metrics defined ad hoc for the smell detection. As outlined in [3] there is the need for a clearer research strategy on smells identification and measurement. Other knowledge has to be exploited for their detection. In this work we are interested to investigate the direct and indirect correlations existing between smells. Moreover we propose to analyze if other relations exist between code smell and another kind of micro structure, called micro pattern[6]. We started this research since we think that the knowledge on these relations between smells could be exploited by code smell detection tools to improve their results. If one code smell exists, this can imply the existence of another code smell, or if one smell exists, another one cannot be there, or perhaps we could observe that some code smells tend to go together. © 2011 IEEE.

ARCELLI FONTANA, F., Zanoni, M. (2011). On investigating code smells correlations. In Proceedings of the IEEE Fourth International Conference on Software Testing, Verification and Validation Workshops (ICSTW) (pp.474-475). IEEE Computer Society [10.1109/ICSTW.2011.14].

On investigating code smells correlations

ARCELLI FONTANA, FRANCESCA;ZANONI, MARCO
2011

Abstract

Code smells are characteristics of the software that may indicate a code or design problem that can make software hard to evolve and maintain. Detecting and removing code smells, when necessary, improves the quality and maintainability of a system. Code smells have been defined in [5], and different detection tools have been developed, each one characterized by particular features and providing often different results. Usually detection techniques are based on the computation of a particular set of combined metrics, or standard object-oriented metrics [8] or metrics defined ad hoc for the smell detection. As outlined in [3] there is the need for a clearer research strategy on smells identification and measurement. Other knowledge has to be exploited for their detection. In this work we are interested to investigate the direct and indirect correlations existing between smells. Moreover we propose to analyze if other relations exist between code smell and another kind of micro structure, called micro pattern[6]. We started this research since we think that the knowledge on these relations between smells could be exploited by code smell detection tools to improve their results. If one code smell exists, this can imply the existence of another code smell, or if one smell exists, another one cannot be there, or perhaps we could observe that some code smells tend to go together. © 2011 IEEE.
paper
code smells; correlation
English
RefTest (REFactoring & TESTing) Berlin Workshop
2011
Proceedings of the IEEE Fourth International Conference on Software Testing, Verification and Validation Workshops (ICSTW)
978-1-4577-0019-4
2011
474
475
5954451
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5954451
none
ARCELLI FONTANA, F., Zanoni, M. (2011). On investigating code smells correlations. In Proceedings of the IEEE Fourth International Conference on Software Testing, Verification and Validation Workshops (ICSTW) (pp.474-475). IEEE Computer Society [10.1109/ICSTW.2011.14].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/35409
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