An Identification Method of Related Group of Threads for a Recent Bug Thread by Peak Characteristics of Similarities

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  • Imanara Yuuki
    Graduate School of Information Science and Technology Osaka University
  • Itakura Kota
    Graduate School of Information Science and Technology Osaka University
  • Samejima Masaki
    Graduate School of Information Science and Technology Osaka University
  • Akiyoshi Masanori
    Graduate School of Information Science and Technology Osaka University

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Other Title
  • 類似度のピーク特性を用いた新規バグスレッドに対する関連スレッド群特定方式
  • ルイジド ノ ピーク トクセイ オ モチイタ シンキ バグスレッド ニ タイスル カンレン スレッドグン トクテイ ホウシキ

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This paper addresses identifying a related group of threads for a recent bug thread posted by a developer in the forum of open source software. A typical approach is to identify as the group of threads that is much similar to the recent bug thread. However, most of recent bug threads that are not related to any groups of threads are wrongly identified. Focusing on the peak characteristics that similarities to related group of threads are much higher than similarities to others, the proposed method identifies whether recent bug threads are related to a group of threads by Support Vector Machine with the peak characteristics of similarities. Experimental results show that the proposed method can keep the recall rate of 76% and improve the precision rate by 49% compared to the method using only thresholds for similarities.

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