https://hackerpaper.kaipfister.de/p/2305.19915/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMThttps://news.ycombinator.com/item?id=38267684urn:hackerpapers:mention:2305.19915:38267684Tue, 14 Nov 2023 18:49:55 GMT<p>A nice survey on Source Code Data Augmentation for Deep Learning. It contains 89 DA papers starting from 2019. It categorizes the existing DA4Code methods and introduces their applications in the various downstream tasks of source code. It also provides a section discussing the challenges and opportunities in the DA4Code domain. It may inspire the community to develop more advanced DA methods for code and find ways to utilize existing techniques. Paper link: https://arxiv.org/abs/2305.19915 GitHub: https://github.com/terryyz/DataAug4Code</p><p><a href="https://hackerpaper.kaipfister.de/p/2305.19915/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.CLhttps://news.ycombinator.com/item?id=38267683urn:hackerpapers:submission:2305.19915:38267683Tue, 14 Nov 2023 18:49:55 GMT<p>Source Code Data Augmentation for Deep Learning: A Survey</p><p></p><p>3 points; 1 discussion reply on HN. <a href="https://hackerpaper.kaipfister.de/p/2305.19915/">Paper and source history</a>. A submission is not an endorsement.</p>cs.CL