Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 134 tok/s
Gemini 2.5 Pro 41 tok/s Pro
GPT-5 Medium 34 tok/s Pro
GPT-5 High 25 tok/s Pro
GPT-4o 69 tok/s Pro
Kimi K2 197 tok/s Pro
GPT OSS 120B 439 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

Developer Load Normalization Using Iterative Kuhn-Munkres Algorithm: An Optimization Triaging Approach (2202.01713v1)

Published 3 Feb 2022 in cs.SE

Abstract: Bug triage can be defined as the process of assigning a developer to a bug report. The duty of the bug triage team is to study the developers profiles well in order to make an appropriate match between the developers and the incoming bug reports. Thus, this process is a vital step in issue management system. In fact, the number of bug reports submitted every day is gradually increasing which affects the developer workload. Thus, the triage team should consider this factor in distributing the bugs and because of the manual approach, many developers are burden. In particular, triaging bug reports without considering the workload does not only affect the developers workload but also leads to an increase in the number of unaddressed bug reports. As a result, the fixing time of the reported bugs will relatively increase. Unlike other researchers who focus on automating the bug triage and ignoring the developer workload, in this work, we handle the triaging process from a different perspective. The proposed approach focuses on how to optimize the bug fixing time by normalizing the developer load in an automating system. To evaluate our work, we use 26,317 bug reports from different bug repositories. Results shows that our work outperforms other systems in terms of optimizing the bug total fixing time and normalizing developer load.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube