e-ISSN:0976-5166
p-ISSN:2231-3850


INDIAN JOURNAL OF COMPUTER SCIENCE AND ENGINEERING

Call for Papers 2020

Jun 2020 - Volume 11, Issue 3
Deadline: 15 May 2020
Due to COVID-19 deadline extended to 31-May-2020
Notification: 15 Jun 2020
Publication: 30 Jun 2020

Aug 2020 - Volume 11, Issue 4
Deadline: 15 Jul 2020
Notification: 15 Aug 2020
Publication: 31 Aug 2020

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ABSTRACT

Title : APPLICATION OF XGBOOST ALGORITHM AND DEEP LEARNING TECHNIQUES FOR SEVERITY ASSESSMENT OF SOFTWARE DEFECT REPORTS
Authors : Ruchika Malhotra, Akanksha Chauhan
Keywords : deep learning; software defects; severity; severity assessment.
Issue Date : May-Jun 2020
Abstract :
Software is present in every aspect of our everyday life, and defects are bound to be found during the testing of the software, no matter how small. It is therefore imperative for software testing engineers to assess the severity of software defects to allocate proper resources for the correction of the defects and prevent software crashes. In this paper, we have proposed the use of the Extreme Gradient Boosting Technique (XGBoost) and deep learning techniques: CNN (Convolutional Neural Network) and RNN (Recurrent Neural Network) to predict the severity of the defects occurring in the software. AUC and sensitivity are the metrics used to evaluate the results. All three techniques: XGBoost algo-rithm, CNN and RNN have performed really well in predicting the severities for all the defects. It has also been noted that XGBoost algorithm is the most efficient in predicting high severity defects, while the performance of deep learning techniques is excellent for the highest as well as the lowest severity defects. For the rest of the severity values, the performance of all the three classifiers is fairly con-sistent.
Page(s) : 267-276
ISSN : 0976-5166
Source : Vol. 11, No.3
PDF : Download
DOI : 10.21817/indjcse/2020/v11i3/201103236