<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Ke Han on Blog | Chameleon</title><link>https://blog.chameleoncloud.org/authors/ke-han/</link><description>Recent content in Ke Han on Blog | Chameleon</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 28 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://blog.chameleoncloud.org/authors/ke-han/index.xml" rel="self" type="application/rss+xml"/><item><title>UpFuzz: Hunting the Data-Format Bugs That Break Distributed-Storage Upgrades</title><link>https://blog.chameleoncloud.org/posts/upfuzz-fuzzing-distributed-storage-upgrade-bugs/</link><pubDate>Thu, 28 May 2026 00:00:00 +0000</pubDate><guid>https://blog.chameleoncloud.org/posts/upfuzz-fuzzing-distributed-storage-upgrade-bugs/</guid><description>&lt;p&gt;Software upgrades are supposed to be routine. In a large data center, thousands of distributed-system upgrades can happen in a single day, each one quietly swapping in new code and migrating the system's stored state from the old version's format to the new one's. Most of the time, no one notices. But when that migration goes wrong, the results can be spectacular — and a team at Purdue University has built a tool, called UpFuzz, designed specifically to catch the failures before they reach production. &lt;strong&gt;The work earned the Community Award at &lt;a href="https://www.usenix.org/conference/nsdi26"&gt;NSDI '26&lt;/a&gt;, USENIX's flagship networked-systems conference as an outstanding paper with publicly available code and data.&lt;/strong&gt;&lt;/p&gt;</description></item></channel></rss>