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Towards just-in-time suggestions for log changes

Heng Li
2018
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The paper empirically studied why developers make log changes and proposed an automated approach to provide developers with log change suggestions as soon as they commit a code change. Through a case study on four open source projects, we found that the reasons for log changes can be grouped along four categories: block change, log improvement, dependence-driven change, and logging issue. We also found that our automated approach can effectively suggest whether a log change is needed for a code change with a balanced accuracy of 0.76 to 0.82.
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