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Abstract:

A great deal of effort has been spent on both trying to specify software requirements and on ensuring that software actually matches these requirements. A wide range of techniques that includes theorem proving, model checking, type-based analysis, static analysis, runtime monitoring, and the like have been proposed. However, in many areas adoption of these techniques remains spotty. In fact, obtaining a specification or a precise notion of correctness is in many cases quite elusive. For many programming tasks, even expert developers are unable to get them right because of numerous tricky corner cases.

In this paper we investigate an approach we call program boosting, which involves crowd-sourcing partially correct solutions to a tricky programming problem from developers and then blending these programs together in a way that improves correctness.

We show how interesting and highly non-trivial programming tasks such as writing regular expressions to match URLs and email addresses can be effectively crowd-sourced. We demonstrate that carefully blending the crowd-sourced results together frequently yields results that are better than any of the individual responses. Our experiments on 465 of programs show consistent boosts in accuracy and demonstrate that program boosting can be performed at a relatively modest monetary cost.

 Bio:

Ben Livshits is a  research scientist at Microsoft Research  in Redmond, WA and  an affiliate professor at  the  University  of  Washington.  Originally  from  St.  Petersburg,  Russia, he received a bachelor’s degree in Computer  Science and Math from  Cornell University in 1999,  and his M.S. and Ph.D.  in Computer  Science from  Stanford University  in 2002  and 2006, respectively. Dr. Livshits’ research interests include application  of sophisticated static and dynamic  analysis techniques to finding errors in programs.

Ben has published papers at PLDI, POPL, Oakland Security, Usenix Security, CCS, SOSP, ICSE, FSE, and many other venues.  He is known  for his work  in software reliability  and especially tools to improve software security, with a primary focus  on approaches to finding buffer overruns in  C programs  and  a  variety  of  security  vulnerabilities (cross-site scripting, SQL injections, etc.)  in  Web-based  applications.  He  is  the  author  of  several dozen academic papers and patents.  Lately, he  has  been  focusing  on topics ranging from security and privacy to crowdsourcing an augmented reality. Ben generally does not speak of himself in the third person.