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Managing technical debt includes the detection and assessment of debt at the code and design levels (such as bad smells). Existing approaches and tools for smell detection primarily use static program data for decision support. While a static analysis allows for identifying smell candidates without executing and instrumenting the system, such approaches also come with the risk of missing candidates or of producing false positives. Moreover, smell candidates might result from a deliberate design decision (e.g., of applying a particular design pattern). Such risks and the general ambivalence of smell detection require a manual design and/or code inspection for reviewing all alleged smells.
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Haendler et al. (2017) studied this question.
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