From Human-to-Human to Human-to-Bot Conversations in Software Engineering

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, also distinguishing between NLU- and LLM-based chatbots. Furthermore, we discuss how understanding the differences among the conversation styles guides the developer on how to shape their expectations from a conversation and consequently support the communication within a software team. We conclude that the recent conversation styles that we observe with LLM-chatbots can not replace conversations with humans due to certain attributes regarding social aspects despite their ability to support productivity and decrease the developers' mental load.