From Human-to-Human to Human-to-Bot Conversations in Software Engineering
Ranim Khojah, Francisco Gomes de Oliveira Neto, Philipp Leitner

TL;DR
This paper explores the differences between human-to-human and human-to-bot conversations in software engineering, analyzing how AI chatbots influence developer interactions and team communication.
Contribution
It adapts conversation attributes to software development and compares human, NLU, and LLM chatbot interactions through an observational study, highlighting their similarities and differences.
Findings
LLM-chatbots exhibit distinct conversation styles from humans.
Chatbots support productivity but cannot replace human social interactions.
Understanding conversation differences guides better integration of chatbots in teams.
Abstract
Software developers use natural language to interact not only with other humans, but increasingly also with chatbots. These interactions have different properties and flow differently based on what goal the developer wants to achieve and who they interact with. In this paper, we aim to understand the dynamics of conversations that occur during modern software development after the integration of AI and chatbots, enabling a deeper recognition of the advantages and disadvantages of including chatbot interactions in addition to human conversations in collaborative work. We compile existing conversation attributes with humans and NLU-based chatbots and adapt them to the context of software development. Then, we extend the comparison to include LLM-powered chatbots based on an observational study. We present similarities and differences between human-to-human and human-to-bot conversations,…
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Taxonomy
TopicsAdvanced Malware Detection Techniques
