https://github.com/samuellucas97/supplementaryinfopackage-slr
https://github.com/samuellucas97/supplementaryinfopackage-slr
large-language-models llm4se software-engineering systematic-literature-reviews
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/samuellucas97/supplementaryinfopackage-slr
- Owner: Samuellucas97
- Created: 2025-03-08T07:33:28.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-03-10T10:00:16.000Z (3 months ago)
- Last Synced: 2025-03-10T10:35:52.857Z (3 months ago)
- Topics: large-language-models, llm4se, software-engineering, systematic-literature-reviews
- Homepage:
- Size: 1.16 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
## Research Artifacts
This is the supplementary material for the SLR on “Junior Software Engineers’ Perspectives on adopting Large Language Models for Development”. This SLR employed the guidelines proposed by Kitchenham et al. We performed a search across 7 digital libraries(ACM DL, IEEE xplore, SpringerLink, Wiley, ScienceDirect, Scopus, and Arxiv). This repository contains:
* SLR Protocol
* SLR Data Extraction Form
* SLR Data
### SLR Protocol
The `SLR_Protocol.pdf` file presents the research methodology applied during the study. It includes:
* Object
* Background
* PICOC
* Research questions
* Base search string
* Search string for each 7 databases
### SLR Data Extraction Form
The `SLR_DataExtractionForm.pdf` file presents the Google forms used for data extraction, containing 36 questions.
### SLR Data
The `SLR_Data.xlsx` file contains all data separated in the following sheets:
* **Included Paper List** sheet: List of all 56 papers and related demographic info.
* **Form Responses** sheet: All the data extracted from the 56 primary studies using google forms.
* **Publication Trends** sheet -- analysis of publication trends (e.g., publication venues, domains) in the 56 selected studies.
* **(RQ1) Motivations and Methodological Approaches** sheet -- has the analysis of data relevant to `RQ1. What are the motivations and methodological approaches behind each primary study to explore the human aspects (e.g., emotion, productivity) of junior software developers adopting LLM-based tools for software development tasks?` and `RQ1a. How are junior software developers classified?` for all the included studies.
* **(RQ2) Key Software Development Tasks** sheet -- has the analysis of data related to `RQ2. What key software development tasks junior developers are using LLM-based tools for?` for all the included studies.
* **(RQ3) Perceptions about LLM4SE** sheet -- has analysis of data relevant to `RQ3. What are the perceptions of junior software developers on using LLM-based tools?` and `RQ3a. What are the perceived and experienced advantages/opportunities of junior software developers on using LLM-based tools?`, `RQ3b. What are the perceived and experienced challenges/limitations faced by junior software developers while using LLM-based tools?`, and `RQ3c. What are the recommendations/best practices suggested by junior software developers while using LLM-based tools?` for all the included studies.
* **(RQ4) Limitations and Future Research Needs** sheet -- has the analysis of data related to `RQ4. What are the limitations and recommendations for future research that we can distil based on the primary studies?` for all the included studies.
### References
Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering.