Efficient Extension of a Software Analysis Framework to Additional Languages

Simple item page
dc.contributor.advisorWalker, Robert James
dc.contributor.authorSoltanpour, Shahryar
dc.contributor.committeememberAycock, John
dc.contributor.committeememberOehlberg, Lora
dc.date2023-11
dc.date.accessioned2023-07-21T16:19:38Z
dc.date.available2023-07-21T16:19:38Z
dc.date.issued2023-07
dc.description.abstractIn the current era of software development, multi-language codebases are common, and change propagation in these codebases is challenging. The existing change propagation tool ModCP is a solution that can assist software developers with propagating changes across several languages, but only one at a time. However, ModCP has some architectural problems in that make supporting new languages hard to develop and maintain for a long time. In addition, supporting change propagation across code snippets consisting of a programming language embedded inside a different programming language would be a useful feature for ModCP. To achieve this, we must detect the embedded code snippets in a code being analyzed by ModCP. In this thesis, we develop a new, more efficient architecture for ModCP, involving a single abstract model that each language extends for its usage, resulting in complete isolation between language results. We compare our approach with a baseline version that uses the same, concrete model for all languages and adds new models when necessary. Our approach reduces code complexity and development time and makes code more compatible with best practices of development compared to the baseline. Moreover, we design a system for ModCP to guess and validate the programming language used in code snippets, based on the initial detection of keywords, as input to execute change propagation for multi-language codes embedded inside each other. We compare our keyword detection approach with existing deep learning and brute force approaches and show that our method is the best choice if accuracy, performance, and scalability are needed simultaneously.
dc.identifier.citationSoltanpour, S. (2023). Efficient extension of a software analysis framework to additional languages (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.
dc.identifier.urihttps://hdl.handle.net/1880/116776
dc.identifier.urihttps://dx.doi.org/10.11575/PRISM/41618
dc.language.isoen
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgary
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.
dc.subjectSoftware Engineering
dc.subjectComputer Science
dc.subjectSoftware Analysis
dc.subjectEmbedded Language Identification
dc.subject.classificationEducation--Technology
dc.titleEfficient Extension of a Software Analysis Framework to Additional Languages
dc.typemaster thesis
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.thesis.accesssetbystudentI do not require a thesis withhold – my thesis will have open access and can be viewed and downloaded publicly as soon as possible.
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ucalgary_2023_soltanpour_shahryar.pdf
Size:
750.53 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.62 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Open Theses and Dissertations