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Deploy to the Crowd; Debug in the Cloud

By Adam J. Oliner and Ion Stoica

Abstract

We propose a method for gathering and analyzing instrumentation data from instances of software running on a large number of clients that aims to facilitate modeling and diagnosis, especially on mobile devices. The method involves a novel combination of dynamic, centrally coordinated instrumentation with collaborative, statistical analyses of both the instances and the environments. This paper describes the method, provides a few example use cases, and outlines some of the research challenges. We believe this proposal is the first to unify correctness, performance, and energy debugging of software deployed to the crowd using a central analysis service based in the cloud. Automated debugging identifies software behavior that violates a specification, which may be explicit or inferred. Acquiring this specification can be challenging. Prior wor

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.353.5265
Provided by: CiteSeerX
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