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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Technical Report: Towards a Universal Code Formatter through Machine Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1606.08866/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1606.08866/feed.xml" rel="self" type="application/rss+xml" /><item><title>Technical Report: Towards a Universal Code Formatter through Machine Learning — mentioned by papa-vova</title><link>https://news.ycombinator.com/item?id=42186644</link><guid isPermaLink="false">urn:hackerpapers:mention:1606.08866:42186644</guid><pubDate>Tue, 19 Nov 2024 18:29:49 GMT</pubDate><description>&lt;p&gt;Speaking of naming: did you guys see this one? https://arxiv.org/abs/1606.08866 And this: https://github.com/antlr/codebuff&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1606.08866/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.PL</category></item><item><title>Technical Report: Towards a Universal Code Formatter through Machine Learning — mentioned by bmc7505</title><link>https://news.ycombinator.com/item?id=22707378</link><guid isPermaLink="false">urn:hackerpapers:mention:1606.08866:22707378</guid><pubDate>Fri, 27 Mar 2020 22:09:58 GMT</pubDate><description>&lt;p&gt;If you enjoyed reading this, you might want to check out CodeBuff: https://github.com/antlr/codebuff CodeBuff is based on a paper by Terrence Parr and Juergen Vinju, “Towards a Universal Code Formatter through Machine Learning”: https://arxiv.org/abs/1606.08866&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1606.08866/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.PL</category></item><item><title>Technical Report: Towards a Universal Code Formatter through Machine Learning — HN submission</title><link>https://news.ycombinator.com/item?id=14104173</link><guid isPermaLink="false">urn:hackerpapers:submission:1606.08866:14104173</guid><pubDate>Thu, 13 Apr 2017 04:30:26 GMT</pubDate><description>&lt;p&gt;Towards a Universal Code Formatter through Machine Learning (2016)&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;74 points; 8 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1606.08866/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.PL</category></item></channel></rss>
