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Study on Automatic Bug Triage using Deep Learning

딥 러닝을 이용한 버그 담당자 자동 배정 연구

  • 이선로 (중앙대학교 컴퓨터공학과) ;
  • 김혜민 (중앙대학교 컴퓨터공학과) ;
  • 이찬근 (중앙대학교 컴퓨터공학부) ;
  • 이기성 (중앙대학교 다빈치교양대학)
  • Received : 2017.04.04
  • Published : 2017.11.15

Abstract

Existing studies on automatic bug triage were mostly used the method of designing the prediction system based on the machine learning algorithm. Therefore, it can be said that applying a high-performance machine learning model is the core of the performance of the automatic bug triage system. In the related research, machine learning models that have high performance are mainly used, such as SVM and Naïve Bayes. In this paper, we apply Deep Learning, which has recently shown good performance in the field of machine learning, to automatic bug triage and evaluate its performance. Experimental results show that the Deep Learning based Bug Triage system achieves 48% accuracy in active developer experiments, un improvement of up to 69% over than conventional machine learning techniques.

Acknowledgement

Supported by : 한국연구재단

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