When Pair Programming Gets Emotional: A Case Study of What LLMs Still Miss

Emotions play a key role in collaborative software practices like pair programming. In this case study, we analyze pair programming videos to assess whether Large Language Models (LLMs) can serve as pair programming partners. We adapt the EmpatheticDialogues benchmark to create scenarios that simulate how an LLM responds in emotional moments in pair programming. We find that LLMs generally match the level of empathy humans provide in emotional moments during pair programming. However, they sometimes get lost in conversational dynamics and miss the big picture, and prioritize task progression over discussion. Our findings highlight both the potential and current limitations of LLMs in emotionally sensitive programming contexts.

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Publication Details

Journal
International Journal of Software Engineering and Knowledge Engineering
Published
2026-04-06
DOI
https://doi.org/10.1142/s0218194026500294
Primary Topic
Software Engineering Techniques and Practices
Type
article
Field-Weighted Citation Impact
0.00

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article

When Pair Programming Gets Emotional: A Case Study of What LLMs Still Miss

Seungmoo Lee, Chi Hyun Cho, Seung Pyo Kang, Jin Ho Jang et al.
International Journal of Software Engineering and Knowledge Engineering
Software Engineering Techniques and Practices
article

When Pair Programming Gets Emotional: A Case Study of What LLMs Still Miss

Seungmoo Lee, Chi Hyun Cho, Seung Pyo Kang, Jin Ho Jang, Kostadin Damevski, Rahat Rizvi Rahman
article en

Abstract

Emotions play a key role in collaborative software practices like pair programming. In this case study, we analyze pair programming videos to assess whether Large Language Models (LLMs) can serve as pair programming partners. We adapt the EmpatheticDialogues benchmark to create scenarios that simulate how an LLM responds in emotional moments in pair programming. We find that LLMs generally match the level of empathy humans provide in emotional moments during pair programming. However, they sometimes get lost in conversational dynamics and miss the big picture, and prioritize task progression over discussion. Our findings highlight both the potential and current limitations of LLMs in emotionally sensitive programming contexts.

International Journal of Software Engineering and Knowledge Engineering
Virginia Commonwealth University (US), Korea National University of Arts (KR)
Korea Creative Content Agency
Openalex Percentile: Top 28%
Software Engineering Techniques and Practices
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