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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Comparison of Various Machine Learning Models For Software Bug Prediction |
| Authors Name: | Shalaka Naik Dessai , Aparna Rane |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_181511
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| Published Paper Id: | IJNRD2206104 |
| Published In: | Volume 7 Issue 6, June-2022 |
| DOI: | |
| Abstract: | As internet users grow, the quantity of data available on the web increases with it. Virtually everything that needs human effort or human presence can be replaced by the Software. While developing an application it follows the Software Development Lifecycle (SDLC). Within the early stages of development, it's a compulsory task to take care of system or bugs to avoid wasting time and effort during initial development phase to forestall any runtime crisis. In this paper , we compare five machine learning models – Logistic Regression, Decision Tree, Random Forest, Adaboost and XGBoost for four datasets of NASA - KC2, PC3, JM1, CM1. Later on, new model was proposed based on tuning the existing XGBoost model by changing its parameter namely N_estimator, learning rate, max depth, and subsample. The results achieved were compared with state-of art models and the results showed that the tuned XGBoost model outperformed them for all datasets. This research will contribute in correctly detecting the bugs with machine learning approach. |
| Keywords: | Machine Learning, Software Bug Prediction, Dataset, Logistic Regression, Decision Tree, Random Forest, Adaboost , XGBoost |
| Cite Article: | "Comparison of Various Machine Learning Models For Software Bug Prediction", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 6, page no.891-898, June-2022, Available :http://www.ijnrd.org/papers/IJNRD2206104.pdf |
| Downloads: | 000118758 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2206104 Registration ID: 181511 Published In: Volume 7 Issue 6, June-2022 DOI (Digital Object Identifier): Page No: 891-898 Country: Cuncolim, Goa, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2206104 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2206104 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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