• Ashwni Kumar
• Mariya Khatoon
• Dr.D.L.Gupta

Predicting software fault is an important part of software engineering. Fault prediction means identifying modules that are prone to failure early in software development. It reduces time, effort and overall costs. Significantly improves the organization's start-up and profits by ensuring customer satisfaction. This field has attracted many researchers over the years to improve the overall quality of the software. Machine learning techniques are the most used techniques in this field today. Machine learning focuses on developing computer programs that may learn to grow and alter once exposed to new information. In this paper, we examine a study of the various software metrics used to predict software fault using machine learning algorithms and we also presented a survey of various machine learning techniques that will help professionals interested build a fault prediction model.

Software Fault Prediction, Machine Learning, Software Metrics, Prediction Techniques.

"Software Fault Prediction Using Machine Learning Approaches: A Survey ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 4, page no.434-438, April 2020, Available :http://www.jetir.org/papers/JETIR2004551.pdf

"Software Fault Prediction Using Machine Learning Approaches: A Survey ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 4, page no. pp434-438, April 2020, Available at : http://www.jetir.org/papers/JETIR2004551.pdf