Software Crash Study

dc.contributor.advisorDumitras, Tudoren_US
dc.contributor.authorZhang, Yantaoen_US
dc.contributor.departmentElectrical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2016-02-09T06:34:58Z
dc.date.available2016-02-09T06:34:58Z
dc.date.issued2015en_US
dc.description.abstractWith the development of personal computers, the user experience has become a vital part of every day work and life of the majority of people on the planet. Hardware components are usually preconfigured and most people tend not to tune them. However, the software environments change much more often because of the configuration by users, the upgrading by vendors and the attacks by hackers. All of those activities can be a factor in the stability of software. In this work, by analyzing a sample of 600,000 machine weeks and around 16,000 applications used on them, we try to derive the relationship between the software environment and the crashes of software. We mainly used association rule mining and analyzed our data on Spark. We also examined the predictability of crashes using the association rules and the difference of predictability between different versions of a same application.en_US
dc.identifierhttps://doi.org/10.13016/M2S42X
dc.identifier.urihttp://hdl.handle.net/1903/17371
dc.language.isoenen_US
dc.subject.pqcontrolledComputer engineeringen_US
dc.subject.pqcontrolledComputer scienceen_US
dc.subject.pquncontrolledAssociation Rule Miningen_US
dc.subject.pquncontrolledCrashen_US
dc.subject.pquncontrolledSoftwareen_US
dc.titleSoftware Crash Studyen_US
dc.typeThesisen_US

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