Mid Sweden University

miun.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Investigating the impact of Generative AI on newcomers' understanding of Software Projects
Mid Sweden University, Faculty of Science, Technology and Media, Department of Communication, Quality Management, and Information Systems (2023-).
Mid Sweden University, Faculty of Science, Technology and Media, Department of Communication, Quality Management, and Information Systems (2023-).
2024 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Context: In both commercial and open-source software development, newcomers often join the development process in the advanced stages of the software development lifecycle. Newcomers frequently face barriers impeding their ability to make early contributions, often caused by a lack of understanding. For this purpose, we have developed an LLM-based tool called SPAC-B that facilitates project-specific question-answering to aid newcomers' understanding of software projects. Objective: Investigate the LLM-based tool's ability to assist newcomers in understanding software projects by measuring its accuracy and conducting an experiment. Method: In this study, a case study is conducted to investigate the accuracy of the tool, measured in relevance, completeness, and correctness. Furthermore, an experiment is performed among software developers to test the tool's ability to help newcomers formulate better plans for open-source issues. Results: SPAC-B achieved an accuracy of 4.60 in relevance, 4.30 in completeness, and 4.28 in correctness on a scale from 1 to 5. It improved the combined mean score of the plans of the 10 participants in our experiments from 1.90 to 2.70, and 8 out of 10 participants found the tool helpful. Conclusions: SPAC-B has demonstrated high accuracy and helpfulness, but further research is needed to confirm if these results can be generalized to a larger population and other contexts of use.

Place, publisher, year, edition, pages
2024. , p. 15
Keywords [en]
Generative AI, LLM, RAG, NLP, Open-source, LangChain, Software project understanding
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:miun:diva-51831OAI: oai:DiVA.org:miun-51831DiVA, id: diva2:1880230
Educational program
Software Engineering TPVAG 120/180 higher education credits
Supervisors
Examiners
Available from: 2024-07-01 Created: 2024-07-01 Last updated: 2024-07-01Bibliographically approved

Open Access in DiVA

fulltext(792 kB)218 downloads
File information
File name FULLTEXT01.pdfFile size 792 kBChecksum SHA-512
9ea687468ad75b69ba41bf993cf761f28616d0addb78ee938c714520a2f12feadda47222a579168ebaec6786e7837c037488c6afeed7d1750ef8c3fdf701ead0
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Larsen, Knud RonauEdvall, Magnus
By organisation
Department of Communication, Quality Management, and Information Systems (2023-)
Software Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 218 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 778 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf