• Anmol Chhabra
• Manmeen Brar

Machine Learning spreads the roots all over the globe and software engineering field is even not exempted from it. Forecasting the software bugs at the beginning phases of the software improves the efficiency, quality, reliability and many other aspects. The designing of software is highly complex which thus needs various guidelines [1]. So, machine learning algorithms use the supervised technique for model building and forecasting the bugs based on the historical data statistics. It thus reduces the development cost of the software. Three major algorithms are used as classifiers - Logistic regression, Decision Tree and Random Forest Classifiers. Hence it results in the model efficiency.

NFRs; IDE; ML

"Forecasting Bugs from the Software using Machine Learning Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.607-610, June-2019, Available :http://www.jetir.org/papers/JETIR1907T59.pdf

"Forecasting Bugs from the Software using Machine Learning Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp607-610, June-2019, Available at : http://www.jetir.org/papers/JETIR1907T59.pdf