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dc.contributor.advisorBarber, Suzanneen
dc.creatorMozano, Ashtonen
dc.date.accessioned2012-02-27T15:12:23Zen
dc.date.available2012-02-27T15:12:23Zen
dc.date.created2011-12en
dc.date.issued2012-02-27en
dc.date.submittedDecember 2011en
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2011-12-4623en
dc.descriptiontexten
dc.description.abstractThe Software Life Cycle (SLC) often comprises a complex sequence of processes, each with many subparts where various execution decisions throughout the pipeline can greatly affect the success or failure of a given project. Some of the most important decisions involve the allocation of scarce resources throughout the SLC, which are often based on estimations about future market demand and various extraneous factors of high stochasticity. Despite numerous efforts in standardization, many projects are still highly dependent on the subjective aptitude of individual managers, who may in turn rely on ad hoc techniques rather than standardized and repeatable ones. The results can be unpredictability and undue reliance on specific individuals. This paper considers imposing a mathematical framework on two of the key aspects of SLC: Deciding how to dynamically allocate available resources throughout the development pipeline, and when to stop further work on a given task in light of the associated Return On Investment (ROI) metrics. In so doing, the software development process is modeled as a problem in New Product Development (NPD) Management, which can be approached using control theory and stochastic combinatorial optimization techniques. The paper begins by summarizing some of the previous developments in these fields, and proposes some future research directions for solving complex resource allocation problems under stochastic settings. The outcome is a formal framework that when combined with competent Configuration Management techniques, can rapidly achieve near-optimal solutions at each stage of the SLC in a standardized manner.en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.subjectControl theoryen
dc.subjectQueueing theoryen
dc.subjectNew product developmenten
dc.subjectSoftware engineeringen
dc.subjectOperations researchen
dc.subjectIndustrial engineeringen
dc.subjectManagementen
dc.titleCtrl.FRAME : a control-theoretical framework for resource allocation management in engineeringen
dc.title.alternativeControl-theoretical framework for resource allocation management in engineeringen
dc.date.updated2012-02-27T15:12:31Zen
dc.identifier.slug2152/ETD-UT-2011-12-4623en
dc.contributor.committeeMemberGraser, Thomasen
dc.description.departmentElectrical and Computer Engineeringen
dc.type.genrethesisen
thesis.degree.departmentElectrical and Computer Engineeringen
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorUniversity of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Science in Engineeringen


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