Studying Duplicate Logging Statements and Their Relationships With Code Clones

In this paper, we focus on studying duplicate logging statements, which are statements that have the same static text message. We manually studied over 4K and their surrounding code in five large-scale open source systems. uncovered patterns of smells. For each instance smell, further identify potentially problematic justifiable cases. Then, contact developers to verify our manual study result. integrated result feedback into automated analysis tool, DLFinder, automatically detects evaluated DLFinder systems three additional total, combining results analysis, reported 91 smell instances all them been fixed. relationship between including smells, clones. find 83% reside cloned code, but 17% micro-clones difficult detect using clone detection tools. also more than half snippets, a large portion very short blocks may not be effectively detected by existing Our shows that, addition general implements business logic, clones bad practices could increase maintenance difficulties.