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dc.contributor.advisorHazlewood, Carol
dc.contributor.authorMichlowitz, Jason Lawrenceen_US
dc.date.accessioned2012-02-24T10:19:12Z
dc.date.available2012-02-24T10:19:12Z
dc.date.issued2006-08-01en_US
dc.date.submittedAugust 2006
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/3911
dc.description.abstractSeveral algorithms that solve different types of problems are implemented, tested, and compared by applying a set of metrics. The results are analyzed using Principal Components Analysis to calculate a Relative Complexity Metric. The results of the study reveal that a programming language does have an effect on the simplicity, speed and other attributes of an implementation. The results of the study also reveal which languages are best suited for a particular type of programming technique, such as recursion.en_US
dc.formatText
dc.format.extent253 pages
dc.format.medium1 file (.pdf)
dc.language.isoen_US
dc.subjectAlgorithmsen_US
dc.subjectSoftware metricsen_US
dc.subjectProgramming languagesen_US
dc.subjectRelative complexity metricen_US
dc.subjectSoftware engineeringen_US
dc.subjectLanguage comparisonsen_US
dc.subjectProgramming problemsen_US
dc.titleA Methodology for Mapping Programming Languages to Programming Problemsen_US
txstate.documenttypeThesis
dc.contributor.committeeMemberPodorozhny, Rodion
dc.contributor.committeeMemberChen, Xiao
thesis.degree.departmentComputer Scienceen_US
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorTexas State Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
txstate.departmentComputer Science


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