An Empirical Study on the Performance of Individual Issue Label Prediction (MSR 2023 - Technical Papers) - MSR 2023

Dates to be announced Melbourne, Australia

co-located with ICSE 2023

Who

Jueun Heo, Seonah Lee

Track

MSR 2023 Technical Papers

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When

Mon 15 May 2023 15:02 - 15:08 at Meeting Room 110 - Understanding Defects Chair(s): Matteo Paltenghi

Abstract

In GitHub, open-source software (OSS) developers label issue reports. As issue labeling is a labor-intensive manual task, automatic approaches have developed to label issue reports. However, those approaches have shown a limited performance. Therefore, it is necessary to analyze the performance of predicting labels for an issue report. Understanding the labels with high performance and those with low performance can help improve the performance of automatic issue labeling tasks. In this paper, we investigate the performance of individual label prediction. Our investigation uncovers labels with high performance and those with low performance. Our results can help researchers to understand the different characteristics of labels and help the developer to develop a unified approach that combines several effective approaches for different kinds of issues.

Jueun Heo

Seonah Lee

Gyeongsang National University

South Korea

Time Zone

The program is currently displayed in (GMT+11:00) Hobart.

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Time Band

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Session Program

Mon 15 May
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	14:20 - 15:15	Understanding DefectsRegistered Reports / Data and Tool Showcase Track / Technical Papers at Meeting Room 110 Chair(s): Matteo Paltenghi University of Stuttgart, Germany

	14:20 12m Talk		What Happens When We Fuzz? Investigating OSS-Fuzz Bug History Technical Papers Brandon Keller Rochester Institute of Technology, Benjamin S. Meyers Rochester Institute of Technology, Andrew Meneely Rochester Institute of Technology
	14:32 12m Talk		An Empirical Study of High Performance Computing (HPC) Performance Bugs Technical Papers Md Abul Kalam Azad University of Michigan - Dearborn, Nafees Iqbal University of Michigan - Dearborn, Foyzul Hassan University of Michigan - Dearborn, Probir Roy University of Michigan at Dearborn Pre-print
	14:44 6m Talk		Semantically-enriched Jira Issue Tracking Data Data and Tool Showcase Track Themistoklis Diamantopoulos Electrical and Computer Engineering Dept, Aristotle University of Thessaloniki, Dimitrios-Nikitas Nastos Electrical and Computer Engineering Dept., Aristotle University of Thessaloniki, Andreas Symeonidis Electrical and Computer Engineering Dept., Aristotle University of Thessaloniki Pre-print
	14:50 6m Talk		An exploratory study of bug introducing changes: what happens when bugs are introduced in open source software? Registered Reports Lukas Schulte Universitity of Passau, Anamaria Mojica-Hanke University of Passau and Universidad de los Andes, Mario Linares-Vasquez Universidad de los Andes, Steffen Herbold University of Passau
	14:56 6m Talk		HasBugs - Handpicked Haskell Bugs Data and Tool Showcase Track Leonhard Applis Delft University of Technology, Annibale Panichella Delft University of Technology
	15:02 6m Talk		An Empirical Study on the Performance of Individual Issue Label Prediction Technical Papers Jueun Heo , Seonah Lee Gyeongsang National University