Scalable Encoding of Modularized Dependency Graphs for Fast Analysis

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dc.contributor.advisorJ. Walker, Robert
dc.contributor.authorSingh, Kanishka
dc.contributor.committeememberElhajj, Reda
dc.contributor.committeememberKrishnamurthy, Diwakar
dc.date2021-11
dc.date.accessioned2021-09-07T14:26:47Z
dc.date.available2021-09-07T14:26:47Z
dc.date.issued2021-08-27
dc.description.abstractSoftware development and analysis tools (SDATs) typically contain complex models that are expensive to compute, and whose expense grows significantly depending on the size of the software system under analysis. When these models are not stored in a manner that allows them to be restored after program restart, that expense is not amortized; re-computation results in undesirable downtime in the developer’s daily workflow. This thesis aims to find the most suitable approach for storing and persisting the models of a specific change propagation tool, ModCP. Existing work to study and identify optimal storage technology has been evaluated using datasets either that are randomly generated---not simulating the nature of real-world software---or that derive from excessively small software systems for which recomputing would be feasible. This thesis explores and implements potentially beneficial datastore technologies in ModCP and compares them on subjective and objective measures against the baseline (time to fully re-building the models) and each other to determine whether storage integration is feasible and significant reduction in the downtime can be achieved. The cost of re-building the model of ModCP can be reduced by 13--46 times, for the datasets we tried, by using specific serialization technology; in contrast, the use of database technologies involves high overhead for read/write queries through database connectors, making them unsuitable as an option for improvement of performance in SDATs.en_US
dc.identifier.citationSingh, K. (2021). Scalable Encoding of Modularized Dependency Graphs for Fast Analysis (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/39159
dc.identifier.urihttp://hdl.handle.net/1880/113816
dc.language.isoengen_US
dc.publisher.facultyScienceen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectChange impact analysisen_US
dc.subjectdependency analysisen_US
dc.subjectmemoizationen_US
dc.subjectserializationen_US
dc.subjectdatabaseen_US
dc.subjectrelational databaseen_US
dc.subjectnon relational databaseen_US
dc.subjectprotobufen_US
dc.subjectjson.neten_US
dc.subjectbinary formatteren_US
dc.subjectMySQLen_US
dc.subjectPostgreSQLen_US
dc.subjectNeo4Jen_US
dc.subjectSoftware engineeringen_US
dc.subjectchange propagationen_US
dc.subject.classificationComputer Scienceen_US
dc.titleScalable Encoding of Modularized Dependency Graphs for Fast Analysisen_US
dc.typemaster thesisen_US
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameMaster of Science (MSc)en_US
ucalgary.item.requestcopytrueen_US
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