Supplementary Dataset for "ChatGPT-Based Best Practices for Pair Programming"

This dataset contains the supplementary materials for the master’s thesis “ChatGPT-Based Best Practices for Pair Programming” by Mehmet Safa Gökalp (Hacettepe University, 2025). It includes evaluation tables, research question (RQ) answer summaries, case study outputs, and systematic literature review (SLR) materials used in the thesis. Specifically, it provides: Rigor and Relevance Evaluation: Scoring of included studies based on context description, study design, validity discussion, and practical relevance. Quality Score of Publication: Assessment of studies using four quality criteria (presentation clarity, average citation per year, research method employed, and quality evaluation degree). RQ Answers Table: Extracted qualitative and quantitative findings mapped to each research question (RQ1–RQ4). Systematic Literature Review Tables: Methodologies, findings, and limitations of reviewed studies. Case Study Data: Includes the submitted code for each programming task and the outcome metrics (test case results, completion time, edge-case handling, solution length, and submission counts). These materials ensure transparency and reproducibility of both the systematic review and the case study process, supporting further research on the use of ChatGPT and large language models in software engineering.