Deep Learning-based Production and Test Bug Report Classification using Source Files (ICSE 2022 - Posters)

Who

Misoo Kim, Youngkyoung Kim, Eunseok Lee

Track

ICSE 2022 Posters

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When

Wed 11 May 2022 03:25 - 03:30 at ICSE Poster room - Poster Session 2 Chair(s): Elena Sherman

Abstract

Classifying production and test bug reports can significantly improve not only the accuracy of performance evaluation but also the performance of information retrieval-based bug localization (IRBL). However, it is time-consuming for developers to classify these bug reports manually. As an alternative, deep learning offers promising solutions for classifying bug reports automatically. This study proposes a production and test bug report classification method based on deep learning. Our method uses a set of source files and model tuning to solve the problem of insufficient and sparse bug reports when applying deep learning. Our experimental results reveal that the macro f1-score of our method is 34% better than that of the classifier trained with only bug reports and can improve the mean average precision of VSM-based IRBL by 22%.

Misoo Kim

Sungkyunkwan University

Youngkyoung Kim

Sungkyunkwan University

Eunseok Lee

Sungkyunkwan University

South Korea

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Session Program

Wed 11 May
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03:00 - 04:00	Poster Session 2Posters at ICSE Poster room Chair(s): Elena Sherman Boise State University

5m Poster		A Static Analyzer for Detecting Tensor Shape Errors in Deep Neural Network Training Code Posters Ho Young Jhoo Seoul National University, Sehoon Kim Seoul National University, Woosung Song Seoul National University, Kyuyeon Park Seoul National University, DongKwon Lee Seoul National University, South Korea, Kwangkeun Yi Seoul National University, South Korea Pre-print
5m Poster		Garuda: Heap aware symbolic execution Posters Ajinkya Rajput , Dr. K. Gopinath Indian Institute of Science, Banglore
5m Poster		The Symptoms, Causes, and Repairs of Workarounds in Apache Issue Trackers Posters Aoyang Yan Shanghai Jiao Tong University, Hao Zhong Shanghai Jiao Tong University, Daohan Song Shanghai Jiao Tong University, Li Jia Shanghai Jiao Tong University
5m Poster		CrystalBLEU: Precisely and Efficiently Measuring the Similarity of Code Posters Aryaz Eghbali University of Stuttgart, Michael Pradel University of Stuttgart
5m Poster		CRISCE: Towards Generating Test Cases from Accident Sketches Posters Vuong Nguyen University of Passau, Alessio Gambi University of Passau, Jasim Ahmed University of Passau, Gordon Fraser University of Passau
5m Poster		Deep Learning-based Production and Test Bug Report Classification using Source Files Posters Misoo Kim Sungkyunkwan University, Youngkyoung Kim Sungkyunkwan University, Eunseok Lee Sungkyunkwan University

Information for Participants

Wed 11 May 2022 03:00 - 04:00 at ICSE Poster room - Poster Session 2 Chair(s): Elena Sherman

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