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Performance of classifiers for SABD reason

Performance of classifiers for SABD reason

Source publication
Performance of classifiers for SABD reason
Frequently occurring n-gram features in each category
Distribution of 'ready-to-be-addressed' SABD
Characterizing and Mitigating Self-Admitted Build Debt
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  • Feb 2021
Technical Debt is a metaphor used to describe the situation in which long-term code quality is traded for short-term goals in software projects. In recent years, the concept of self-admitted technical debt (SATD) was proposed, which focuses on debt that is intentionally introduced and described by developers. Although prior work has made important...
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Context 1
... 5: The auto-sklearn classifier tends to outperform the baseline classifiers for both reasons and purposes. Table 4 shows the classifier performance with respect to the reasons for SABD. The table shows that the average precision is 0.68, which is greater than the precision of the NB and kNN classifiers (0.57 and 0.62, respectively). ...
Context 2
... RQ2, we propose automatic classifiers to identify SABD characteristics. Tables 4 and 5 show that our classifiers are promising. The result demonstrates the feasibility of automatic classifiers and serves as a key step for developing a SABD classification system. ...

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Characterizing and Mitigating Self-Admitted Technical Debt in Build Systems
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Technical Debt is a metaphor used to describe the situation in which long-term software artifact quality is traded for short-term goals in software projects. In recent years, the concept of self-admitted technical debt (SATD) was proposed, which focuses on debt that is intentionally introduced and described by developers. Although prior work has ma...
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