Show simple item record

dc.contributor.authorTansey, Wesleyen_US
dc.date.accessioned2014-03-14T20:38:48Z
dc.date.available2014-03-14T20:38:48Z
dc.date.issued2008-05-22en_US
dc.identifier.otheretd-05272008-161318en_US
dc.identifier.urihttp://hdl.handle.net/10919/33292
dc.description.abstractIn modern software development, maintenance accounts for the majority of the total cost and effort in a software project. Especially burdensome are those tasks which require applying a new technology in order to adapt an application to changed requirements or a different environment. This research explores methodologies, techniques, and approaches for automating such adaptive maintenance tasks. By combining high-level specifications and generative techniques, a new methodology shapes the design of approaches to automating adaptive maintenance tasks in the application domains of high performance computing (HPC) and enterprise software. Despite the vast differences of these domains and their respective requirements, each approach is shown to be effective at alleviating their adaptive maintenance burden. This thesis proves that it is possible to effectively automate tedious and error-prone adaptive maintenance tasks in a diverse set of domains by exploiting high-level specifications to synthesize specialized low-level code. The specific contributions of this thesis are as follows: (1) a common methodology for designing automated approaches to adaptive maintenance, (2) a novel approach to automating the generation of efficient marshaling logic for HPC applications from a high-level visual model, and (3) a novel approach to automatically upgrading legacy enterprise applications to use annotation-based frameworks. The technical contributions of this thesis have been realized in two software tools for automated adaptive maintenance: MPI Serializer, a marshaling logic generator for MPI applications, and Rosemari, an inference and transformation engine for upgrading enterprise applications. This thesis is based on research papers accepted to IPDPS '08 and OOPSLA '08.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartthesis.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectAdaptive Maintenanceen_US
dc.subjectSoftware Maintenanceen_US
dc.subjectUpgradingen_US
dc.subjectMarshalingen_US
dc.subjectHPCen_US
dc.subjectProgram Synthesisen_US
dc.subjectFrameworksen_US
dc.subjectMetadataen_US
dc.titleAutomated Adaptive Software Maintenance: A Methodology and Its Applicationsen_US
dc.typeThesisen_US
dc.contributor.departmentComputer Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
dc.contributor.committeechairTilevich, Elien_US
dc.contributor.committeememberRibbens, Calvin J.en_US
dc.contributor.committeememberBack, Godmar V.en_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05272008-161318/en_US
dc.date.sdate2008-05-27en_US
dc.date.rdate2008-08-11
dc.date.adate2008-08-11en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record