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dc.contributor.advisorSivakumar, Raghupathy
dc.contributor.authorWang, Jiechao
dc.date.accessioned2013-09-27T14:38:01Z
dc.date.available2013-09-27T14:38:01Z
dc.date.issued2013-05-15
dc.identifier.urihttp://hdl.handle.net/1853/49142
dc.description.abstractIn this thesis, we focused on two problems in mobile application development: contextualization and large-scale testing. We identified the limitations of current contextualization and testing solutions. On one hand, advanced-remote-computing- based mobilization does not provide context awareness to the mobile applications it mobilized, so we presented contextify to provide context awareness to them without rewriting the applications or changing their source code. Evaluation results and user surveys showed that contextify-contextualized applications reduce users' time and effort to complete tasks. On the other hand, current mobile application testing solutions cannot conduct tests at the UI level and in a large-scale manner simultaneously, so we presented and implemented automated cloud computing (ACT) to achieve this goal. Evaluation results showed that ACT can support a large number of users and it is stable, cost-efficiency as well as time-efficiency.
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectContextualization
dc.subjectLarge-scale testing
dc.subjectMobile apps
dc.subject.lcshContext-aware computing
dc.subject.lcshMobile computing
dc.subject.lcshCloud computing
dc.subject.lcshWeb applications
dc.titleApproaches for contextualization and large-scale testing of mobile applications
dc.typeThesis
dc.description.degreeM.S.
dc.contributor.departmentElectrical and Computer Engineering
dc.contributor.committeeMemberAl-Regib, Ghassan
dc.contributor.committeeMemberBeyah, Raheem


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