Transfer Learning for Software Engineering:
Tim Menzies, Fayola Peters
A Literature Review
Lane Department of CS & EE, WVU, USA
Forrest Shull, Lucas Layman
Fraunhofer Center for Experimental SE, College Park, MD, USA
Recently, there has been much success with automatic transfer learning between SE projects. This short paper reviews that work to observe that (1) transfer learning has been far more successful at transferring lessons learned than traditional SE methods; (2) past research on transfer learning has uncovered numerous issues and open issues that need exploring.
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