Search Results for author:
Found 9 papers, 0 papers with code
Multi-line AI-assisted Code Authoring
In this paper, we present how we scaled the product from displaying single-line suggestions to multi-line suggestions.
AI-assisted Code Authoring at Scale: Fine-tuning, deploying, and mixed methods evaluation
At the time of this writing, 16K developers have used it with 8% of their code coming directly from CodeCompose.
Code Smells in Machine Learning Systems
We found that our newly identified code smells are prevalent and impactful on the maintenance of DL systems from the developer's perspective.
ConE: A Concurrent Edit Detection Tool for Large Scale Software Development
We study half a year of changes made to six large repositories in Microsoft in which at least 1, 000 pull requests are created each month.
SoftNER: Mining Knowledge Graphs From Cloud Incidents
We have deployed SoftNER at Microsoft, a major cloud service provider and have evaluated it on more than 2 months of cloud incidents.
Nudge: Accelerating Overdue Pull Requests Towards Completion
The key novelty of Nudge is that it succeeds in reducing pull request resolution time, while ensuring that developers perceive the notifications sent as useful, at the scale of thousands of repositories.
Neural Knowledge Extraction From Cloud Service Incidents
Prior work on incident management has been heavily focused on the challenges with incident triaging and de-duplication.
An Empirical Study of Software Exceptions in the Field using Search Logs
Using the machine learning model, we extracted exceptions from raw queries and performed popularity, effort, success, query characteristic and web domain analysis.
Analyzing Web Search Behavior for Software Engineering Tasks
Subsequently, we propose a taxonomy of intents to identify the various contexts in which web search is used in software engineering.
