Result: A Review Paper on Software Defect Prediction Based on Rule Mining

Title:
A Review Paper on Software Defect Prediction Based on Rule Mining
Authors:
Fareha Bashir, Dr. Akbar Shaun
Source:
International Journal of Engineering and Management Research; Vol. 13 No. 2 (2023): April Issue; 220-224
Publisher Information:
Vandana Publications, 2023.
Publication Year:
2023
Subject Terms:
Software Defect Prediction, Classification Algorithm, Rule Mining, Confusion Matrix
Document Type:
Academic journal Article
File Description:
application/pdf
Language:
English
DOI:
10.31033/ijemr.13.2.37
Access URL:
https://ijemr.vandanapublications.com/index.php/j/article/view/1225
Rights:
CC BY
Accession Number:
edsair.issn22500758..315b70b04f164e8547f86b9e0b436a1f
Database:
OpenAIRE

Further Information

Software defect prediction is an important task in software engineering, aimed at identifying and mitigating software defects before they become major problems. Rule mining is a technique used to discover interesting patterns and relationships in data, and can be applied to software defect prediction by analyzing past data on software development and testing. This abstract discusses the process of software defect prediction based on rule mining, including data collection, data pre-processing, feature extraction, rule mining, model evaluation, and model deployment. By accurately predicting the likelihood of defects occurring in future software releases, developers can take proactive measures to prevent defects from occurring, thereby improving software quality and reducing the time and resources spent on fixing bugs.