# Exploring Context-Aware Conversational Agents in Software Development

arXiv: https://arxiv.org/abs/2006.02370 · HTML: https://mlsanity.com/paper/2006.02370/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jun 2020.

## Built on by (most cited first, 3 of 3)

- [A Literature Survey of Recent Advances in Chatbots](https://mlsanity.com/paper/2201.06657/) (2022)
- [Beyond Code Generation: An Observational Study of ChatGPT Usage in Software Engineering Practice](https://mlsanity.com/paper/2404.14901/) (2024)
- [An Approach for Auto Generation of Labeling Functions for Software Engineering Chatbots](https://mlsanity.com/paper/2410.07094/) (2024)

## Abstract (arXiv)

Software development is a complex endeavor that depends on a wide variety of contextual factors involving a large amount of distributed information. This knowledge could include: technology-related tasks, software operating environments and stakeholder requirements. A major roadblock to using this knowledge in software development is that most of this information is implicit and captured in the developers' minds (tacit) or spread through volumes of documentation. Developers, as they work often have to maintain mental models of these tasks as they produce the software. As a result, context can be easily lost or forgotten and developers often use trial-and-error approaches while finishing the project. This study aims at analyzing whether supporting software developers with a chatbot during task execution can improve the overall development experience. The chatbot can assist the developers in executing different tasks based on implicit contextual information. We propose an implementation to explore the viability of using textual chatbots to assist developers automatically and proactively with software development project activities that recur.