Using Static Analysis to Diagnose Misconfigured Open Source Systems Software

Ten years ago, few software developers worked on distributed systems. Today, developers often run code on clusters, relying on large open-source software stacks to manage resources. These systems are challenging to configure and debug. Fortunately, developments in program analysis have given us new tools for managing the complexity of modern software. This talk will show how static analysis can help users configure their systems. I present a technique that builds an explicit table mapping a program's possible error messages to the options that might cause them. As a result, users can get immediate feedback on how to resolve configuration errors.

Ariel Rabkin is a fifth (and final)-year PhD candidate in the RAD Lab at UC Berkeley, working with Randy Katz. He is formerly from Cornell University, AB 2006, MEng 2007). He is interested in software quality and software intelligibility. He expects to graduate in May 2012. His dissertation is about applying program analysis to system management, including automatically describing program configuration options and diagnosing configuration errors. He is a contributor to several open source projects, including Hadoop, the Chukwa log collection framework, and the JChord program analysis toolset.