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Found 7 papers, 0 papers with code
Can GPT-4 Replicate Empirical Software Engineering Research?
We specifically study their ability to surface assumptions made in empirical software engineering research methodologies, as well as their ability to plan and generate code for analysis pipelines on seven empirical software engineering papers.
Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
In this work, we do the first large-scale study to evaluate the effectiveness of these models for helping engineers root cause and mitigate production incidents.
Anomalicious: Automated Detection of Anomalous and Potentially Malicious Commits on GitHub
Security is critical to the adoption of open source software (OSS), yet few automated solutions currently exist to help detect and prevent malicious contributions from infecting open source repositories.
Software Engineering
"How Was Your Weekend?" Software Development Teams Working From Home During COVID-19
The first, an exploratory survey during the early months of the pandemic with 2, 265 developer responses, revealed that many developers faced challenges reaching milestones and that their team productivity had changed.
Software Engineering
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.
