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A Novel Deep-Learning-Based Bug Severity Classification Technique Using Convolutional Neural Networks and Random

Ashima Kukkar1, Rajni Mohana1, Anand Nayyar2

  • 1Department of Computer Science Jaypee University of Information Technology, Waknaghat 173 234, India.

Sensors (Basel, Switzerland)
|July 10, 2019
PubMed
Summary
This summary is machine-generated.

A novel deep learning model, Bug Severity classification (BCR), accurately classifies bug report severity. Using Convolutional Neural Network and Random Forest with Boosting, BCR enhances bug triage efficiency and outperforms existing methods.

Keywords:
convolutional neural networkdeep learningn-gramnatural language processingrandom forestseverity classificationsoftware reliability

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Area of Science:

  • Software Engineering
  • Artificial Intelligence
  • Machine Learning

Background:

  • Bug report severity classification is crucial for efficient bug fixing.
  • Rapidly growing bug repositories introduce biases in bug triage.
  • Existing machine learning models lack accuracy due to insufficient feature extraction.

Purpose of the Study:

  • To propose a novel deep learning model for automated bug severity classification.
  • To address the limitations of existing models in handling large bug repositories.
  • To improve the accuracy and efficiency of the bug triage process.

Main Methods:

  • Preprocessing bug report text using natural language techniques.
  • Feature extraction using n-gram.
  • Utilizing a Convolutional Neural Network (CNN) for feature pattern extraction.
  • Classifying multiple bug severity classes with Random Forest with Boosting (BCR).

Main Results:

  • The proposed BCR model achieved an average accuracy of 96.34% on multiclass severity classification across five open-source projects.
  • BCR demonstrated an average F-measure of 96.43% for binary class severity classification, significantly outperforming existing approaches (84.24%).

Conclusions:

  • The BCR model effectively learns latent and representative features for accurate bug severity classification.
  • The proposed approach significantly enhances bug severity classification performance compared to state-of-the-art techniques.
  • BCR offers a robust solution for balancing the bug triage process in large-scale software development.