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Automatic Bug Priority Prediction Using DNN Based Regression

  • Wei ZhangEmail author
  • Chris Challis
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1074)

Abstract

Bugs are inevitable during software development. It is important to prioritize bugs and fix them based on their priorities. The priority assignment is usually done manually. Besides the cost of human effort, this process may also introduce bias since different people might have different opinions on the same issue. In this paper, we propose an approach to automate the process. It builds features from bug reports using Natural Language Processing, then trains a predictive model based on a deep Neural Network. The proposed approach was tested using a comprehensive data set containing more than 82 thousand bug reports. It runs in near real-time and its performance is significantly better than the previously reported results.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Adobe Systems Inc.McLeanUSA

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