Applied Deep Code Search for Algorithm Implementation using Pseudocode

dc.contributor.author Valluri, Sai Charishma
dc.contributor.committeeMember Li, Qi
dc.contributor.majorProfessor Le, Wei
dc.date.accessioned 2022-06-08T16:00:39Z
dc.date.available 2022-06-08T16:00:39Z
dc.date.copyright 2022
dc.date.issued 2022-05
dc.description.abstract Code retrieval tools and techniques play a key role in facilitating the software developers to retrieve code snippets from open-source projects given a natural language query. With natural language description as an input, the code search tool searches for the most relevant code snippets amongst the code. This creative component focuses on training the state-of-the-art code search tool, Deep Code Search, with the dataset of algorithms as a source code and studying the resultant code snippets when given the pseudo-code as an input query. We trained the Deep Code Search for three different programming language settings, Java, C, and a combination of Java and C. Our results show that Deep Code Search can identify the algorithm implementation in different languages for the given pseudo-code.
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/105346
dc.language.iso en_US
dc.rights.holder Sai Charishma Valluri
dc.subject.keywords Code Search
dc.subject.keywords Algorithm Implementation using Pseudocode
dc.subject.keywords Algorithm Search on Codebase
dc.title Applied Deep Code Search for Algorithm Implementation using Pseudocode
dc.type Text
dc.type.genre creativecomponent
dspace.entity.type Publication
relation.isDegreeOrgUnitOfPublication f7be4eb9-d1d0-4081-859b-b15cee251456
thesis.degree.department Computer Science
thesis.degree.discipline Computer Science
thesis.degree.level Masters
thesis.degree.name Master of Science
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