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• W2132201370 abstract "There are various activities that support software maintenance. Program comprehension and detection of design anomalies and their symptoms, like code smells and anti patterns, are particularly relevant for improving the quality and facilitating evolution of a system. In this paper we describe an empirical study on the detection of code smells, aiming at identifying the most frequent smells in systems of different domains and hence the domains characterized by more smells. Moreover, we study possible correlations existing among smells and the values of a set of software quality metrics using Spearman's rank correlation and Principal Component Analysis." @default.
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• W2132201370 date "2013-09-01" @default.
• W2132201370 modified "2023-10-12" @default.
• W2132201370 title "Investigating the Impact of Code Smells on System's Quality: An Empirical Study on Systems of Different Application Domains" @default.
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• W2132201370 doi "https://doi.org/10.1109/icsm.2013.37" @default.
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