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Soft Computing and Machine Intelligence Journal 

Towards Effective Analysis and Tracking of Mozilla and Eclipse Defects using Machine Learning Models based on Bugs Data

Author(s): Zohaib Hassan (a)*, Naeem Iqbal (a) and Abnash Zaman (b).
(a) FSRA&IT Solutions Providing Organization Peshawar, Pakistan
(b) Faculty of Bioinformatics Shaheed Benazeer Bhutto Women University Peshawar, Pakistan
* Corresponding author ✉: Dev.zohaibmrt@hotmail.com

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Publication year: 2021

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article as:

Hassan , Z., Iqbal , N., & Zaman , A. (2021). Towards Effective Analysis and Tracking of Mozilla and Eclipse Defects using Machine Learning Models based on Bugs Data. Soft Computing and Machine Intelligence Journal, 1(1), 1-10.


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