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Automatic Bug Priority Prediction Using DNN Based Regression

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Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((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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Notes

  1. 1.

    When the accuracy is at \(69\%\), if all misassigned labels were off by 2 levels, MAE would be \(0.69 \times 0 + 0.31 \times 2 = 0.62\). If all misassigned labels were off by just 1 level, MAE = \(0.69 \times 0 + 0.31 \times 2 = 0.31\). We achieved 0.39, which is very close to 0.31. With some simple calculation, this means that at least \(75\%\) of the wrong prediction results are off by only one level.

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Authors and Affiliations

  1. Adobe Systems Inc., McLean, VA, 22102, USA

    Wei Zhang & Chris Challis

Authors
  1. Wei Zhang
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  2. Chris Challis
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Corresponding author

Correspondence to Wei Zhang .

Editor information

Editors and Affiliations

  1. School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yong Liu

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Lipo Wang

  3. Computer Science and Mathematics, University of Sao Paulo, Ribeirao Preto, Brazil

    Liang Zhao

  4. School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China

    Zhengtao Yu

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Zhang, W., Challis, C. (2020). Automatic Bug Priority Prediction Using DNN Based Regression. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1074. Springer, Cham. https://doi.org/10.1007/978-3-030-32456-8_36

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