Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Software Engineering

arXiv:2305.00886 (cs)
[Submitted on 1 May 2023]

Title:Designing Adaptive Developer-Chatbot Interactions: Context Integration, Experimental Studies, and Levels of Automation

Authors:Glaucia Melo
View PDF
Abstract:The growing demand for software developers and the increasing development complexity have emphasized the need for support in software engineering projects. This is especially relevant in light of advancements in artificial intelligence, such as conversational systems. A significant contributor to the complexity of software development is the multitude of tools and methods used, creating various contexts in which software developers must operate. Moreover, there has been limited investigation into the interaction between context-based chatbots and software developers through experimental user studies. Assisting software developers in their work becomes essential. In particular, understanding the context surrounding software development and integrating this context into chatbots can lead to novel insight into what software developers expect concerning these human-chatbot interactions and their levels of automation. In my research, I study the design of context-based adaptive interactions between software developers and chatbots to foster solutions and knowledge to support software developers at work.
Comments: Accepted at the 2023 ICSE Doctoral Symposium
Subjects: Software Engineering (cs.SE)
Cite as: arXiv:2305.00886 [cs.SE]
  (or arXiv:2305.00886v1 [cs.SE] for this version)
  https://doi.org/10.48550/arXiv.2305.00886

Submission history

From: Glaucia Melo [view email]
[v1] Mon, 1 May 2023 15:37:39 UTC (710 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
view license
Current browse context:
cs.SE
< prev   |   next >
new | recent | 2023-05
Change to browse by:
cs

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)