Computer program complexity and its correlation with program features and sociolinguistics

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dc.contributor.authorAlam, Sowkat
dc.contributor.authorUniversity of Lethbridge. Faculty of Arts and Science
dc.contributor.supervisorRice, Jacqueline E.
dc.date.accessioned2021-01-07T16:36:21Z
dc.date.available2021-01-07T16:36:21Z
dc.date.issued2021
dc.degree.levelMastersen_US
dc.description.abstractMachine learning techniques have been widely used to understand the use of various sociolinguistic characteristics. These techniques can also be applied to analyze artificial languages. This research focuses on the influence of socio-characteristics, especially region and gender, on an artificial language (programming language). Software complexity features, 103 programming features, and their correlations (using pearson correlation) are also explored in this work. Machine learning and statistical techniques are used to determine whether any dissimilarities or similarities exist in the use of C++ programming language. We show that machine learning models can predict the region of programmers with 78.36\% accuracy and the gender of programmers with 62.63\% accuracy. We hypothesize that feature frequency difference may be a reason for lower accuracy in the gender-based program classification. We also demonstrate that some features such as for-loops and if-else conditions are closely correlated to the complexity of a computer program.en_US
dc.description.sponsorshipNatural Sciences and Engineering Research Council (NSERC) of Canada and the University of Lethbridge, Alberta, Canada.en_US
dc.identifier.urihttps://hdl.handle.net/10133/5818
dc.language.isoen_USen_US
dc.proquest.subjectComputer science [0984]en_US
dc.proquest.subjectArtificial intelligence [0800]en_US
dc.proquest.subjectComputer engineering [0464]en_US
dc.proquestyesYesen_US
dc.publisherLethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Scienceen_US
dc.publisher.departmentDepartment of Mathematics & Computer Scienceen_US
dc.publisher.facultyArts and Scienceen_US
dc.relation.ispartofseriesThesis (University of Lethbridge. Faculty of Arts and Science)en_US
dc.subjectArtificial intelligenceen_US
dc.subjectComputer programmingen_US
dc.subjectDissertations, Academicen_US
dc.subjectMachine learningen_US
dc.subjectProgramming (Computers)en_US
dc.subjectProgramming languages (Computers)en_US
dc.subjectSociolinguisticsen_US
dc.titleComputer program complexity and its correlation with program features and sociolinguisticsen_US
dc.typeThesisen_US
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